Scalable and Fault Tolerant Group Key Management
To address the group key management problem for modern networks this research proposes a lightweight group key management protocol with a gossip-based dissemination routine. Experiments show that by slightly increasing workload for the key update mechanism, this protocol is superior to currently available tree-based protocols with respect to reliability and fault tolerance, while remaining scalable to large groups. In addition, it eliminates the need for logical key hierarchy while preserving an overall reduction in rekey messages to rekey a group. The protocol provides a simple "pull" mechanism to ensure perfect rekeys in spite of the primary rekey mechanism's probabilistic guarantees, without burdening key distribution facilities. Benefits of this protocol are quantified versus tree-based dissemination in Java simulations on networks exhibiting various node failure rates.This work has been selected by scholars as being culturally important, and is part of the knowledge base of civilization as we know it. This work was reproduced from the original artifact, and remains as true to the original work as possible. Therefore, you will see the original copyright references, library stamps (as most of these works have been housed in our most important libraries around the world), and other notations in the work.This work is in the public domain in the United States of America, and possibly other nations. Within the United States, you may freely copy and distribute this work, as no entity (individual or corporate) has a copyright on the body of the work.As a reproduction of a historical artifact, this work may contain missing or blurred pages, poor pictures, errant marks, etc. Scholars believe, and we concur, that this work is important enough to be preserved, reproduced, and made generally available to the public. We appreciate your support of the preservation process, and thank you for being an important part of keeping this knowledge alive and relevant.
Using Sequence Analysis to Perform Application-Based Anomaly Detection Within an Artificial Immune System Framework
The Air Force and other Department of Defense (DoD) computer systems typically rely on traditional signature-based network IDSs to detect various types of attempted or successful attacks. Signature-based methods are limited to detecting known attacks or similar variants; anomaly-based systems, by contrast, alert on behaviors previously unseen. The development of an effective anomaly-detecting, application-based IDS would increase the Air Force's ability to ward off attacks that are not detected by signature-based network IDSs, thus strengthening the layered defenses necessary to acquire and maintain safe, secure communication capability. This system follows the Artificial Immune System (AIS) framework, which relies on a sense of "self," or normal system states to determine potentially dangerous abnormalities ("non-self").This work has been selected by scholars as being culturally important, and is part of the knowledge base of civilization as we know it. This work was reproduced from the original artifact, and remains as true to the original work as possible. Therefore, you will see the original copyright references, library stamps (as most of these works have been housed in our most important libraries around the world), and other notations in the work.This work is in the public domain in the United States of America, and possibly other nations. Within the United States, you may freely copy and distribute this work, as no entity (individual or corporate) has a copyright on the body of the work.As a reproduction of a historical artifact, this work may contain missing or blurred pages, poor pictures, errant marks, etc. Scholars believe, and we concur, that this work is important enough to be preserved, reproduced, and made generally available to the public. We appreciate your support of the preservation process, and thank you for being an important part of keeping this knowledge alive and relevant.
Digital Warfare
Digital Data Warfare (DDW) is an emerging field that has great potential as a means to meet military, political, economic, and personal objectives. Distinguished from the "hacker" variety of malicious computer code, by its predictable nature and the ability to target specific systems, DDW provides the hacker with the means to deny, degrade, decieve, and/or exploit a targeted system. The five phases of DDW attack--penetration, propogation, dormancy, execution, and termination, are presented for the first time by the author in this paper. The nature allows it to be used in the stategic, operational, and tactical warfare roles. Three questions should be considered when developing a strategy for employing DDW: (1) Who should control the employment of DDW? (2) What types of systems should be targeted, and (3) Under what circumstances should DDW be used? Finally, a brief overview of possible countermeasures against DDW is provided as well as an outline of an effective information system security program that would provide a defense against DDW.This work has been selected by scholars as being culturally important, and is part of the knowledge base of civilization as we know it. This work was reproduced from the original artifact, and remains as true to the original work as possible. Therefore, you will see the original copyright references, library stamps (as most of these works have been housed in our most important libraries around the world), and other notations in the work.This work is in the public domain in the United States of America, and possibly other nations. Within the United States, you may freely copy and distribute this work, as no entity (individual or corporate) has a copyright on the body of the work.As a reproduction of a historical artifact, this work may contain missing or blurred pages, poor pictures, errant marks, etc. Scholars believe, and we concur, that this work is important enough to be preserved, reproduced, and made generally available to the public. We appreciate your support of the preservation process, and thank you for being an important part of keeping this knowledge alive and relevant.
Suspicion Modeling in Support of Cyber-Influence Operations/Tactics
Understanding the cognitive process of IT user suspicion may assist organizations in development of network protection plans, personnel training, and tools necessary to identify and mitigate nefarious intrusions IT systems. Exploration of a conceptual common ground between psycho-social and technology-related concepts of suspicion are the heart of this investigation. The complexities involvedd in merging these perspectivess led to the overall questrion: What is the nature of the suspicion towrds IT? The research problem/ phenomenon wasaddress via extensive liteaturereview, and use of the Interactvie Qualitative Analysis methodogly. A problem/phenomenon. Analysis of the system led tot he development of a model of IT suspicion as a progenitor for future experimental constructs that measure or assess behavior as a result of cyber attacks.This work has been selected by scholars as being culturally important, and is part of the knowledge base of civilization as we know it. This work was reproduced from the original artifact, and remains as true to the original work as possible. Therefore, you will see the original copyright references, library stamps (as most of these works have been housed in our most important libraries around the world), and other notations in the work.This work is in the public domain in the United States of America, and possibly other nations. Within the United States, you may freely copy and distribute this work, as no entity (individual or corporate) has a copyright on the body of the work.As a reproduction of a historical artifact, this work may contain missing or blurred pages, poor pictures, errant marks, etc. Scholars believe, and we concur, that this work is important enough to be preserved, reproduced, and made generally available to the public. We appreciate your support of the preservation process, and thank you for being an important part of keeping this knowledge alive and relevant.
Passwords
The purpose of this research was to see how individuals use and remember passwords. Specifically, this thesis sought to answer research questions addressing if organizational parameters are influencing behaviors associated with password choice and to what effect. Volunteers answered the research questions via a web-survey. The research identified the need for an evaluation of how organizations limit password choice by setting parameters for individuals.This work has been selected by scholars as being culturally important, and is part of the knowledge base of civilization as we know it. This work was reproduced from the original artifact, and remains as true to the original work as possible. Therefore, you will see the original copyright references, library stamps (as most of these works have been housed in our most important libraries around the world), and other notations in the work.This work is in the public domain in the United States of America, and possibly other nations. Within the United States, you may freely copy and distribute this work, as no entity (individual or corporate) has a copyright on the body of the work.As a reproduction of a historical artifact, this work may contain missing or blurred pages, poor pictures, errant marks, etc. Scholars believe, and we concur, that this work is important enough to be preserved, reproduced, and made generally available to the public. We appreciate your support of the preservation process, and thank you for being an important part of keeping this knowledge alive and relevant.
Formal Mitigation Strategies for the Insider Threat
The advancement of technology and reliance on information systems have fostered an environment of sharing and trust. The rapid growth and dependence on these systems, however, creates an increased risk associated with the insider threat. The insider threat is one of the most challenging problems facing the security of information systems because the insider already has capabilities within the system. Despite research efforts to prevent and detect insiders, organizations remain susceptible to this threat because of inadequate security policies and a willingness of some individuals to betray their organization. To investigate these issues, a formal security model and risk analysis framework are used to systematically analyze this threat and develop effective mitigation strategies. This research extends the Schematic Protection Model to produce the first comprehensive security model capable of analyzing the safety of a system against the insider threat. The model is used to determine vulnerabilities in security policies and system implementation. Through analysis, mitigation strategies that effectively reduce the threat are identified. Furthermore, an action-based taxonomy that expresses the insider threat through measurable and definable actions is presented.This work has been selected by scholars as being culturally important, and is part of the knowledge base of civilization as we know it. This work was reproduced from the original artifact, and remains as true to the original work as possible. Therefore, you will see the original copyright references, library stamps (as most of these works have been housed in our most important libraries around the world), and other notations in the work.This work is in the public domain in the United States of America, and possibly other nations. Within the United States, you may freely copy and distribute this work, as no entity (individual or corporate) has a copyright on the body of the work.As a reproduction of a historical artifact, this work may contain missing or blurred pages, poor pictures, errant marks, etc. Scholars believe, and we concur, that this work is important enough to be preserved, reproduced, and made generally available to the public. We appreciate your support of the preservation process, and thank you for being an important part of keeping this knowledge alive and relevant.
Establishing the Human Firewall
Hackers frequently use social engineering attacks to gain a foothold into a target network. This type of attack is a tremendous challenge to defend against, as the weakness lies in the human users, not in the technology. Thus far, methods for dealing with this threat have included establishing better security policies and educating users on the threat that exists. Existing techniques aren't working as evidenced by the fact that auditing agencies consider it a given that will be able to gain access via social engineering. The purpose of this research is to propose a better method of reducing an individual's vulnerability to social engineering attacks.This work has been selected by scholars as being culturally important, and is part of the knowledge base of civilization as we know it. This work was reproduced from the original artifact, and remains as true to the original work as possible. Therefore, you will see the original copyright references, library stamps (as most of these works have been housed in our most important libraries around the world), and other notations in the work.This work is in the public domain in the United States of America, and possibly other nations. Within the United States, you may freely copy and distribute this work, as no entity (individual or corporate) has a copyright on the body of the work.As a reproduction of a historical artifact, this work may contain missing or blurred pages, poor pictures, errant marks, etc. Scholars believe, and we concur, that this work is important enough to be preserved, reproduced, and made generally available to the public. We appreciate your support of the preservation process, and thank you for being an important part of keeping this knowledge alive and relevant.
Multi-Class Classification for Identifying JPEG Steganography Embedding Methods
Over 725 steganography tools are available over the Internet, each providing a method for covert transmission of secret messages. This research presents four steganalysis advancements that result in an algorithm that identifies the steganalysis tool used to embed a secret message in a JPEG image file. The algorithm includes feature generation, feature preprocessing, multi-class classification and classifier fusion. The first contribution is a new feature generation method which is based on the decomposition of discrete cosine transform (DCT) coefficients used in the JPEG image encoder. The generated features are better suited to identifying discrepancies in each area of the decomposed DCT coefficients. Second, the classification accuracy is further improved with the development of a feature ranking technique in the preprocessing stage for the kernel Fisher's discriminant (KFD) and support vector machines (SVM) classifiers in the kernel space during the training process. Third, for the KFD and SVM two-class classifiers a classification tree is designed from the kernel space to provide a multi-class classification solution for both methods. Fourth, by analyzing a set of classifiers, signature detectors, and multi-class classification methods a classifier fusion system is developed to increase the detection accuracy of identifying the embedding method used in generating the steganography images.This work has been selected by scholars as being culturally important, and is part of the knowledge base of civilization as we know it. This work was reproduced from the original artifact, and remains as true to the original work as possible. Therefore, you will see the original copyright references, library stamps (as most of these works have been housed in our most important libraries around the world), and other notations in the work.This work is in the public domain in the United States of America, and possibly other nations. Within the United States, you may freely copy and distribute this work, as no entity (individual or corporate) has a copyright on the body of the work.As a reproduction of a historical artifact, this work may contain missing or blurred pages, poor pictures, errant marks, etc. Scholars believe, and we concur, that this work is important enough to be preserved, reproduced, and made generally available to the public. We appreciate your support of the preservation process, and thank you for being an important part of keeping this knowledge alive and relevant.
An Artificial Immune System-Inspired Multiobjective Evolutionary Algorithm With Application to the Detection of Distributed Computer Network Intrusions
Today's predominantly-employed signature-based intrusion detection systems are reactive in nature and storage-limited. Their operation depends upon catching an instance of an intrusion or virus after a potentially successful attack, performing post-mortem analysis on that instance and encoding it into a signature that is stored in its anomaly database. The time required to perform these tasks provides a window of vulnerability to DoD computer systems. Further, because of the current maximum size of an Internet Protocol-based message, the database would have to be able to maintain 25665535 possible signature combinations. In order to tighten this response cycle within storage constraints, this thesis presents an Artificial Immune System-inspired Multiobjective Evolutionary Algorithm intended to measure the vector of tradeoff solutions among detectors with regard to two independent objectives: best classification fitness and optimal hypervolume size. Modeled in the spirit of the human biological immune system and intended to augment DoD network defense systems, our algorithm generates network traffic detectors that are dispersed throughout the network.This work has been selected by scholars as being culturally important, and is part of the knowledge base of civilization as we know it. This work was reproduced from the original artifact, and remains as true to the original work as possible. Therefore, you will see the original copyright references, library stamps (as most of these works have been housed in our most important libraries around the world), and other notations in the work.This work is in the public domain in the United States of America, and possibly other nations. Within the United States, you may freely copy and distribute this work, as no entity (individual or corporate) has a copyright on the body of the work.As a reproduction of a historical artifact, this work may contain missing or blurred pages, poor pictures, errant marks, etc. Scholars believe, and we concur, that this work is important enough to be preserved, reproduced, and made generally available to the public. We appreciate your support of the preservation process, and thank you for being an important part of keeping this knowledge alive and relevant.
Software Protection Against Reverse Engineering Tools
Advances in technology have led to the use of simple to use automated debugging tools which can be extremely helpful in troubleshooting problems in code. However, a malicious attacker can use these same tools. Securely designing software and keeping it secure has become extremely difficult. These same easy to use debuggers can be used to bypass security built into software. While the detection of an altered executable file is possible, it is not as easy to prevent alteration in the first place. One way to prevent alteration is through code obfuscation or hiding the true function of software so as to make alteration difficult. This research executes blocks of code in parallel from within a hidden function to obscure functionality.This work has been selected by scholars as being culturally important, and is part of the knowledge base of civilization as we know it. This work was reproduced from the original artifact, and remains as true to the original work as possible. Therefore, you will see the original copyright references, library stamps (as most of these works have been housed in our most important libraries around the world), and other notations in the work.This work is in the public domain in the United States of America, and possibly other nations. Within the United States, you may freely copy and distribute this work, as no entity (individual or corporate) has a copyright on the body of the work.As a reproduction of a historical artifact, this work may contain missing or blurred pages, poor pictures, errant marks, etc. Scholars believe, and we concur, that this work is important enough to be preserved, reproduced, and made generally available to the public. We appreciate your support of the preservation process, and thank you for being an important part of keeping this knowledge alive and relevant.
An Application of Automated Theorem Provers to Computer System Security
The Schematic Protection Model is specified in SAL and theorems about Take-Grant and New Technology File System schemes are proven. Arbitrary systems can be specified in SPM and analyzed. This is the first known automated analysis of SPM specifications in a theorem prover. The SPM specification was created in such a way that new specifications share the underlying framework and are configurable within the specifications file alone. This allows new specifications to be created with ease as demonstrated by the four unique models included within this document. This also allows future users to more easily specify models without recreating the framework. The built-in modules of SAL provided the needed support to make the model flexible and entities asynchronous. This flexibility allows for the number of entities to be dynamic and to meet the needs of different specifications. The models analyzed in this research demonstrate the validity of the specification and its application to real-world systems.This work has been selected by scholars as being culturally important, and is part of the knowledge base of civilization as we know it. This work was reproduced from the original artifact, and remains as true to the original work as possible. Therefore, you will see the original copyright references, library stamps (as most of these works have been housed in our most important libraries around the world), and other notations in the work.This work is in the public domain in the United States of America, and possibly other nations. Within the United States, you may freely copy and distribute this work, as no entity (individual or corporate) has a copyright on the body of the work.As a reproduction of a historical artifact, this work may contain missing or blurred pages, poor pictures, errant marks, etc. Scholars believe, and we concur, that this work is important enough to be preserved, reproduced, and made generally available to the public. We appreciate your support of the preservation process, and thank you for being an important part of keeping this knowledge alive and relevant.
Defensive Cyber Battle Damage Assessment Through Attack Methodology Modeling
Due to the growing sophisticated capabilities of advanced persistent cyber threats, it is necessary to understand and accurately assess cyber attack damage to digital assets. This thesis proposes a Defensive Cyber Battle Damage Assessment (DCBDA) process which utilizes the comprehensive understanding of all possible cyber attack methodologies captured in a Cyber Attack Methodology Exhaustive List (CAMEL). This research proposes CAMEL to provide detailed knowledge of cyber attack actions, methods, capabilities, forensic evidence and evidence collection methods. This product is modeled as an attack tree called the Cyber Attack Methodology Attack Tree (CAMAT). The proposed DCBDA process uses CAMAT to analyze potential attack scenarios used by an attacker. These scenarios are utilized to identify the associated digital forensic methods in CAMEL to correctly collect and analyze the damage from a cyber attack. The results from the experimentation of the proposed DCBDA process show the process can be successfully applied to cyber attack scenarios to correctly assess the extent, method and damage caused by a cyber attack.This work has been selected by scholars as being culturally important, and is part of the knowledge base of civilization as we know it. This work was reproduced from the original artifact, and remains as true to the original work as possible. Therefore, you will see the original copyright references, library stamps (as most of these works have been housed in our most important libraries around the world), and other notations in the work.This work is in the public domain in the United States of America, and possibly other nations. Within the United States, you may freely copy and distribute this work, as no entity (individual or corporate) has a copyright on the body of the work.As a reproduction of a historical artifact, this work may contain missing or blurred pages, poor pictures, errant marks, etc. Scholars believe, and we concur, that this work is important enough to be preserved, reproduced, and made generally available to the public. We appreciate your support of the preservation process, and thank you for being an important part of keeping this knowledge alive and relevant.
A Distributed Agent Architecture for a Computer Virus Immune System
Information superiority is identified as an Air Force core competency and is recognized as a key enabler for the success of future missions. Information protection and information assurance are vital components required for achieving superiority in the Infosphere, but these goals are threatened by the exponential birth rate of new computer viruses. The increased global interconnectivity that is empowering advanced information systems is also increasing the spread of malicious code and current anti-virus solutions are quickly becoming overwhelmed by the burden of capturing and classifying new viral stains. To overcome this problem, a distributed computer virus immune system (CVIS) based on biological strategies is developed. The biological immune system (BIS) offers a highly parallel defense-in-depth solution for detecting and eliminating foreign invaders. Each component of the BIS can be viewed as an autonomous agent. Only through the collective actions of this multi-agent system can non-self entities be detected and removed from the body. This research develops a model of the BIS and utilizes software agents to implement a CVIS. The system design validates that agents are an effective methodology for the construction of an artificial immune system largely because the biological basis for the architecture can be described as a system of collaborating agents. The distributed agent architecture provides support for detection and management capabilities that are unavailable in current anti-virus solutions. However, the slow performance of the Java and the Java Shared Data Toolkit implementation indicate the need for a compiled language solution and the importance of understanding the performance issues in agent system design. The detector agents are able to distinguish self from non-self within a probabilistic error rate that is tunable through the proper selection of system parameters. This research also shows that by fighting viruses using an immune system model, tThis work has been selected by scholars as being culturally important, and is part of the knowledge base of civilization as we know it. This work was reproduced from the original artifact, and remains as true to the original work as possible. Therefore, you will see the original copyright references, library stamps (as most of these works have been housed in our most important libraries around the world), and other notations in the work.This work is in the public domain in the United States of America, and possibly other nations. Within the United States, you may freely copy and distribute this work, as no entity (individual or corporate) has a copyright on the body of the work.As a reproduction of a historical artifact, this work may contain missing or blurred pages, poor pictures, errant marks, etc. Scholars believe, and we concur, that this work is important enough to be preserved, reproduced, and made generally available to the public. We appreciate your support of the preservation process, and thank you for being an important part of keeping this knowledge alive and relevant.
Mission Assurance
Military organizations have embedded information technology (IT) into mission processes to increase operational efficiency, improve decision-making quality, and shorten the sensor-to-shooter cycle. This IT-to-mission dependence can place the organizational mission at risk when an information incident (e.g., loss or manipulation of an information resource) occurs. Non-military organizations typically address this type of IT risk through an introspective, enterprise-wide focused risk management program that continuously identifies, prioritizes, and documents risks so control measures may be selected and implemented.This work has been selected by scholars as being culturally important, and is part of the knowledge base of civilization as we know it. This work was reproduced from the original artifact, and remains as true to the original work as possible. Therefore, you will see the original copyright references, library stamps (as most of these works have been housed in our most important libraries around the world), and other notations in the work.This work is in the public domain in the United States of America, and possibly other nations. Within the United States, you may freely copy and distribute this work, as no entity (individual or corporate) has a copyright on the body of the work.As a reproduction of a historical artifact, this work may contain missing or blurred pages, poor pictures, errant marks, etc. Scholars believe, and we concur, that this work is important enough to be preserved, reproduced, and made generally available to the public. We appreciate your support of the preservation process, and thank you for being an important part of keeping this knowledge alive and relevant.
A Dynamically Configurable Log-Based Distributed Security Event Detection Methodology Using Simple Event Correlator
This research effort identifies attributes of distributed event correlation which make it desirable for security event detection, and evaluates those attributes in a comparison with a centralized alternative. Event correlation is an effective means of detecting complex situations encountered in information technology environments. Centralized, database-driven log event correlation is more commonly implemented, but suffers from flaws such as high network bandwidth utilization, significant requirements for system resources, and difficulty in detecting certain suspicious behaviors. This analysis measures the value in distributed event correlation by considering network bandwidth utilization, detection capability and database query efficiency, as well as through the implementation of remote configuration scripts and correlation of multiple log sources. These capabilities produce a configuration which allows a 99% reduction of network syslog traffic in the low-accountability case, and a significant decrease in database execution time through context-addition in the high-accountability case.This work has been selected by scholars as being culturally important, and is part of the knowledge base of civilization as we know it. This work was reproduced from the original artifact, and remains as true to the original work as possible. Therefore, you will see the original copyright references, library stamps (as most of these works have been housed in our most important libraries around the world), and other notations in the work.This work is in the public domain in the United States of America, and possibly other nations. Within the United States, you may freely copy and distribute this work, as no entity (individual or corporate) has a copyright on the body of the work.As a reproduction of a historical artifact, this work may contain missing or blurred pages, poor pictures, errant marks, etc. Scholars believe, and we concur, that this work is important enough to be preserved, reproduced, and made generally available to the public. We appreciate your support of the preservation process, and thank you for being an important part of keeping this knowledge alive and relevant.
Development of a Methodology for Customizing Insider Threat Auditing on a Linux Operating System
Insider threats can pose a great risk to organizations and by their very nature are difficult to protect against. Auditing and system logging are capabilities present in most operating systems and can be used for detecting insider activity. However, current auditing methods are typically applied in a haphazard way, if at all, and are not conducive to contributing to an effective insider threat security policy. This research develops a methodology for designing a customized auditing and logging template for a Linux operating system. An intent-based insider threat risk assessment methodology is presented to create use case scenarios tailored to address an organization's specific security needs and priorities. These organization specific use cases are verified to be detectable via the Linux auditing and logging subsystems and the results are analyzed to create an effective auditing rule set and logging configuration for the detectable use cases. Results indicate that creating a customized auditing rule set and system logging configuration to detect insider threat activity is possible.This work has been selected by scholars as being culturally important, and is part of the knowledge base of civilization as we know it. This work was reproduced from the original artifact, and remains as true to the original work as possible. Therefore, you will see the original copyright references, library stamps (as most of these works have been housed in our most important libraries around the world), and other notations in the work.This work is in the public domain in the United States of America, and possibly other nations. Within the United States, you may freely copy and distribute this work, as no entity (individual or corporate) has a copyright on the body of the work.As a reproduction of a historical artifact, this work may contain missing or blurred pages, poor pictures, errant marks, etc. Scholars believe, and we concur, that this work is important enough to be preserved, reproduced, and made generally available to the public. We appreciate your support of the preservation process, and thank you for being an important part of keeping this knowledge alive and relevant.
Metamorphic Program Fragmentation as a Software Protection
Unauthorized reverse-engineering of programs and algorithms is a major problem for the software industry. Every program released to the public can be analyzed by any number of malicious reverse-engineers. These reversers search for security holes in the program to exploit or try to steal a competitor's vital algorithms. While it can take years and millions of dollars worth of research to develop new software, a determined reverser can reverse-engineer the program in a fraction of the time. To discourage reverse-engineering attempts, developers use a variety of software prote tions to obfuscate their programs. However, these protections are generally static, allowing reverse-engineers to eventually adapt to the protections, defeat them, and sometimes build automated tools to defeat them in the future. Metamorphic software protections add another layer of protection to traditional static obfuscation techniques. Metamorphic protections force a reverser to adjust their attacks as the protection changes. Program fragmentation combines two obfuscation techniques, outlining and obfuscated jump tables, into a new, metamorphic protection. Sections of code are removed from the main program flow and randomly placed throughout memory, reducing the programs locality. These fragments move while the program is running and are called using obfuscated jump tables, making program execution difficult to follow. This research assesses the performance overhead of a program fragmentation metamorphic engine and provides a qualitative analysis of its effectiveness against reverse-engineering techniques. Program fragmentation has very little associated overhead, with execution times for individual fragments of less than one microsecond. This low overhead allow a large numbers of fragments to be inserted into programs for protection. In addition, program fragmentation is an effective technique to complicate program of programs using two common disassembler/debugger tools. Thus, program fraThis work has been selected by scholars as being culturally important, and is part of the knowledge base of civilization as we know it. This work was reproduced from the original artifact, and remains as true to the original work as possible. Therefore, you will see the original copyright references, library stamps (as most of these works have been housed in our most important libraries around the world), and other notations in the work.This work is in the public domain in the United States of America, and possibly other nations. Within the United States, you may freely copy and distribute this work, as no entity (individual or corporate) has a copyright on the body of the work.As a reproduction of a historical artifact, this work may contain missing or blurred pages, poor pictures, errant marks, etc. Scholars believe, and we concur, that this work is important enough to be preserved, reproduced, and made generally available to the public. We appreciate your support of the preservation process, and thank you for being an important part of keeping this knowledge alive and relevant.
Using a Distributed Object-Oriented Database Management System in Support of a High-Speed Network Intrusion Detection System Data Repository
The Air Force has multiple initiatives to develop data repositories for high-speed network intrusion detection systems (IDS). All of the developed systems utilize a relational database management system (RDBMS) as the primary data storage mechanism. The purpose of this thesis is to replace the RDBMS in one such system developed by AFRL, the Automated Intrusion Detection Environment (AIDE), with a distributed object-oriented database management system (DOODBMS) and observe a number of areas: its performance against the RDBMS in terms of IDS event insertion and retrieval, the distributed aspects of the new system, and the resulting object-oriented architecture. The resulting system, the Object-Oriented Automated Intrusion Detection Environment (OOAIDE), is designed, built, and tested using the DOODBMS Objectivity/DB. Initial tests indicate that the new system is remarkably faster than the original system in terms of event insertion. Object retrievals are also faster when more than one association is used in the query. The database is then replicated and distributed across a simple heterogeneous network with preliminary tests indicating no loss of performance. A standardized object model is also presented that can accommodate any IDS data repository built around a DOODBMS architecture.This work has been selected by scholars as being culturally important, and is part of the knowledge base of civilization as we know it. This work was reproduced from the original artifact, and remains as true to the original work as possible. Therefore, you will see the original copyright references, library stamps (as most of these works have been housed in our most important libraries around the world), and other notations in the work.This work is in the public domain in the United States of America, and possibly other nations. Within the United States, you may freely copy and distribute this work, as no entity (individual or corporate) has a copyright on the body of the work.As a reproduction of a historical artifact, this work may contain missing or blurred pages, poor pictures, errant marks, etc. Scholars believe, and we concur, that this work is important enough to be preserved, reproduced, and made generally available to the public. We appreciate your support of the preservation process, and thank you for being an important part of keeping this knowledge alive and relevant.
Bubble World a Novel Visual Information Retrieval Technique
With the tremendous growth of published electronic information sources in the last decade and the unprecedented reliance on this information to succeed in day-to-day operations, comes the expectation of finding the right information at the right time. Sentential interfaces are currently the only viable solution for searching through large infospheres of unstructured information, however, the simplistic nature of their interaction model and lack of cognitive amplification they can provide severely limit the performance of the interface. Visual information retrieval systems are emerging as possible candidate replacements for the more traditional interfaces, but many lack the cognitive framework to support the knowledge crystallization process found to be essential in information retrieval. This work introduces a novel visual information retrieval technique crafted from two distinct design genres: (1) the cognitive strategies of the human mind to solve problems and (2) observed interaction patterns with existing information retrieval systems. Based on the cognitive and interaction framework developed in this research, a functional prototype information retrieval system, called Bubble World, has been created to demonstrate that significant performance gains can be achieved using this technique when compared to more traditional text-based interfaces.This work has been selected by scholars as being culturally important, and is part of the knowledge base of civilization as we know it. This work was reproduced from the original artifact, and remains as true to the original work as possible. Therefore, you will see the original copyright references, library stamps (as most of these works have been housed in our most important libraries around the world), and other notations in the work.This work is in the public domain in the United States of America, and possibly other nations. Within the United States, you may freely copy and distribute this work, as no entity (individual or corporate) has a copyright on the body of the work.As a reproduction of a historical artifact, this work may contain missing or blurred pages, poor pictures, errant marks, etc. Scholars believe, and we concur, that this work is important enough to be preserved, reproduced, and made generally available to the public. We appreciate your support of the preservation process, and thank you for being an important part of keeping this knowledge alive and relevant.
Spear Phishing Attack Detection
This thesis addresses the problem of identifying email spear phishing attacks, which are indicative of cyber espionage. Spear phishing consists of targeted emails sent to entice a victim to open a malicious file attachment or click on a malicious link that leads to a compromise of their computer. Current detection methods fail to detect emails of this kind consistently. The SPEar phishing Attack Detection system (SPEAD) is developed to analyze all incoming emails on a network for the presence of spear phishing attacks. SPEAD analyzes the following file types: Windows Portable Executable and Common Object File Format (PE/COFF), Adobe Reader, and Microsoft Excel, Word, and PowerPoint. SPEAD's malware detection accuracy is compared against five commercially-available email anti-virus solutions. Finally, this research quantifies the time required to perform this detection with email traffic loads emulating an Air Force base network. Results show that SPEAD outperforms the anti-virus products in PE/COFF malware detection with an overall accuracy of 99.68% and an accuracy of 98.2% where new malware is involved. Additionally, SPEAD is comparable to the anti-virus products when it comes to the detection of new Adobe Reader malware with a rate of 88.79%. Ultimately, SPEAD demonstrates a strong tendency to focus its detection on new malware, which is a rare and desirable trait. Finally, after less than 4 minutes of sustained maximum email throughput, SPEAD's non-optimized configuration exhibits one-hour delays in processing files and links.This work has been selected by scholars as being culturally important, and is part of the knowledge base of civilization as we know it. This work was reproduced from the original artifact, and remains as true to the original work as possible. Therefore, you will see the original copyright references, library stamps (as most of these works have been housed in our most important libraries around the world), and other notations in the work.This work is in the public domain in the United States of America, and possibly other nations. Within the United States, you may freely copy and distribute this work, as no entity (individual or corporate) has a copyright on the body of the work.As a reproduction of a historical artifact, this work may contain missing or blurred pages, poor pictures, errant marks, etc. Scholars believe, and we concur, that this work is important enough to be preserved, reproduced, and made generally available to the public. We appreciate your support of the preservation process, and thank you for being an important part of keeping this knowledge alive and relevant.
Developing a Corpus Specific Stop-List Using Quantitative Comparison
We have become overwhelmed with electronic information and it seems our situation is not going to improve. When computers first became thought of as instruments to assist us and make our lives easier we thought of a future, that would be a manageable one. We envisioned a day when documents, no matter when they were produced, would be as close as a click of the mouse and the typing of a few words. Locating information of interest was not going to take all day. What we have found is technology changes faster than we can keep up with it. This thesis will look at how we can provide faster access to the information we are looking for. Previous research in the area of document/information retrieval has mainly focused on the automated creation of abstracts and indexes. But today's requirements are more closely related to searching for information through the use of queries. At the heart of the query process is the removal of search terms with little or no significance to the search being performed. More often than not stop-lists are constructed from the most commonly occurring words in the English language. This approach may be fine for systems, which handle information from very broad categories.This work has been selected by scholars as being culturally important, and is part of the knowledge base of civilization as we know it. This work was reproduced from the original artifact, and remains as true to the original work as possible. Therefore, you will see the original copyright references, library stamps (as most of these works have been housed in our most important libraries around the world), and other notations in the work.This work is in the public domain in the United States of America, and possibly other nations. Within the United States, you may freely copy and distribute this work, as no entity (individual or corporate) has a copyright on the body of the work.As a reproduction of a historical artifact, this work may contain missing or blurred pages, poor pictures, errant marks, etc. Scholars believe, and we concur, that this work is important enough to be preserved, reproduced, and made generally available to the public. We appreciate your support of the preservation process, and thank you for being an important part of keeping this knowledge alive and relevant.
Cryptanalysis of Pseudorandom Number Generators in Wireless Sensor Networks
This work presents a brute-force attack on an elliptic curve cryptosystemimplemented on UC Berkley's TinyOS operating system for wireless sensor networks.The attack exploits the short period of the pseudorandom number generator (PRNG) usedby the cryptosystem to generate private keys. The attack assumes a laptop is listeningpromiscuously to network traffic for key messages and requires only the sensor node'spublic key and network address to discover the private key. Experimental results showthat roughly 50% of the address space leads to a private key compromise in 25 minuteson average.This work has been selected by scholars as being culturally important, and is part of the knowledge base of civilization as we know it. This work was reproduced from the original artifact, and remains as true to the original work as possible. Therefore, you will see the original copyright references, library stamps (as most of these works have been housed in our most important libraries around the world), and other notations in the work.This work is in the public domain in the United States of America, and possibly other nations. Within the United States, you may freely copy and distribute this work, as no entity (individual or corporate) has a copyright on the body of the work.As a reproduction of a historical artifact, this work may contain missing or blurred pages, poor pictures, errant marks, etc. Scholars believe, and we concur, that this work is important enough to be preserved, reproduced, and made generally available to the public. We appreciate your support of the preservation process, and thank you for being an important part of keeping this knowledge alive and relevant.
Microsoft Security Copilot
Become a Security Copilot expert and harness the power of AI to stay ahead in the evolving landscape of cyber defenseKey Features: - Explore the Security Copilot ecosystem and learn to design effective prompts, promptbooks, and custom plugins- Apply your knowledge with real-world case studies that demonstrate Security Copilot in action- Transform your security operations with next-generation defense capabilities and automation- Access interactive learning paths and GitHub-based examples to build practical expertiseBook Description: Be at the forefront of cybersecurity innovation with Microsoft Security Copilot, where advanced AI tackles the intricate challenges of digital defense. This book unveils Security Copilot's powerful features, from AI-powered analytics revolutionizing security operations to comprehensive orchestration tools streamlining incident response and threat management. Through real-world case studies and frontline stories, you'll learn how to truly harness AI advancements and unlock the full potential of Security Copilot within the expansive Microsoft ecosystem.Designed for security professionals navigating increasingly sophisticated cyber threats, this book equips you with the skills to accelerate threat detection and investigation, refine your security processes, and optimize cyber defense strategies.By the end of this book, you'll have become a Security Copilot ninja, confidently crafting effective prompts, designing promptbooks, creating custom plugins, and integrating logic apps for enhanced automation.What You Will Learn: - Navigate and use the complete range of features in Microsoft Security Copilot- Unlock the full potential of Security Copilot's diverse plugin ecosystem- Strengthen your prompt engineering skills by designing impactful and precise prompts- Create and optimize promptbooks to streamline security workflows- Build and customize plugins to meet your organization's specific needs- See how AI is transforming threat detection and response for the new era of cyber defense- Understand Security Copilot's pricing model for cost-effective solutionsWho this book is for: This book is for cybersecurity professionals at all experience levels, from beginners seeking foundational knowledge to seasoned experts looking to stay ahead of the curve. While readers with basic cybersecurity knowledge will find the content approachable, experienced practitioners will gain deep insights into advanced features and real-world applications.Table of Contents- Elevating Cyber Defense with Security Copilot- Unveiling Security Copilot through Its Embedded Experience- Navigating the Security Copilot Platform- Extending Security Copilot's Capabilities with Plugins- The Art of Prompt Engineering- The Power of Promptbooks in Security Copilot- Automation and Integration - The Next Frontier- Cyber Sleuthing with Security Copilot- Harnessing Security Copilot within the Microsoft Ecosystem- Frontline Tales with Security Copilot- The Pricing Model in Security Copilot
SEO Training 2017
SEO Training 2017: Search Engine Optimization for Small BusinessLearn practical SEO principles, tactics and concepts from Zhelinrentice L. Scott (the SEO Queen) to start generating the results and exposure you want from your small business marketing online.Are you struggling to: -Understand how search engines work?-Beat your competitors' rankings on Google, Bing or Yahoo?-Generate qualified traffic for your products, services or solutions? -Increase awareness and market share of what you offer online?-Monetize your website and leverage Google's Algorithms?If you answered YES to at least 3 of the questions above, then " SEO Training in 2017: Search Engine Optimization for Small Business" is the seo book for you. This unique practical guide is packed with powerful and effective exercises and activities for you to apply on your website to prove to yourself that what Zhe shares in her book - works.No fluff. No spin. No padding......Just real, practical, solid SEO information and advice that guarantees to help improve your rankings while mastering seo.In " SEO Training 2017: Search Engine Optimization and Marketing for Small Business" you will learn: -What a search is and what it is not-How to leverage News results to beat your competitor's rankings-How to leverage image results to get more exposure for your products online-5 quick steps to Master video marketing to improve your SEO results -Powerful and practical Geo targeting methods that can greatly help retail businesses-Why a PULL approach can be 520% more effective than a PUSH approach with SEO-Which keywords prospects are typing into google to find your competitors-The best keywords that can turn your website into a client magnet-Discover the power of long tail keywords and how they can improve conversions by 150% or more-How to track every single online promotion and campaign you do online-How to adapt for each SEO algorithm update to ensure your website is never penalised.-The power of anchor text and how to pull hungry pre-qualified buyers to your site-8 of the most powerful social media strategies that help buyers find and engage with you-Learn how to build your very best backlinks to boost your website's visibility. In " SEO Training in 2017: Search Engine Optimization for Small Business" you will also learn how to: -Save time and man hours with vital keyword research to find SEO opportunities -Improve efficiency and ROI by taking control of your own SEO marketing and not 3rd party suppliers -Generate more visibility online with 12 powerful on page tactics you can immediately use on your site-Improve Cash flow & Profitability reducing or eliminating unnecessary online marketing costs-Grow Your Business Online by running multiple SEO campaigns for multiple pages and websitesStill Not Sure? Then ask yourself: Are you happy with...-The current Return on Investment from your website? -your existing SEO rankings on the search engines? -the level of sales, and revenue that you're generating from your website? -Your current market share and findability locally, nationally or internationally online?If you answered NO to any of these, then start to grow your business online with this seo guide book NOW.Let's make 2017 your best year yet - online FREE BONUSReceive a FREE mystery bonus worth $250.00 with a complimentary voucher enclosed in the book.Buy this Book NOW & generate better Google SEO results before your online competitors do!
Forest Health Monitoring Using AI and Remote Sensing
Scientific Study from the year 2025 in the subject Computer Sciences - Artificial Intelligence, language: English, abstract: Forest ecosystems play a pivotal role in global ecological stability, biodiversity conservation, and climate regulation. Monitoring forest health is critical to combating deforestation, disease outbreaks, and climate-induced stressors. This book presents the integration of Artificial Intelligence (AI) and Remote Sensing (RS) technologies as transformative tools for forest health monitoring. The book explores AI-based approaches, data fusion techniques, satellite and UAV applications, and real-world case studies, highlighting the potential for predictive, scalable, and real-time ecosystem management. Forests are indispensable components of Earth's ecological and climatic systems, serving as critical reservoirs of biodiversity, carbon sinks, and providers of ecosystem services. However, they are increasingly threatened by deforestation, climate-induced stressors, pest outbreaks, and anthropogenic disturbances. Traditional forest health monitoring methods-such as manual ground surveys and visual inspections-are labor-intensive, limited in spatial and temporal scope, and often insufficient for large-scale, dynamic assessments. Recent advancements in Artificial Intelligence (AI) and Remote Sensing (RS) technologies have enabled transformative approaches to monitoring forest health with improved scalability, accuracy, and temporal frequency. This book investigates the synergistic integration of AI and RS for comprehensive forest health monitoring. Key themes include the use of satellite and Unmanned Aerial Vehicle (UAV) platforms, spectral and thermal indices, machine learning and deep learning algorithms, and real-world applications in detecting deforestation, disease outbreaks, and drought stress. By leveraging multisource data fusion and AI-driven analytics, forest monitoring systems can achieve predictive, automated, and near real-time capabil
Energy and Throughput Optimization in NB-IoT Networks
This book focuses on enhancing energy efficiency and network throughput in Narrowband IoT (NB-IoT) and Narrowband Cognitive Radio IoT (NB-CR-IoT) networks. A three-hop assignment using a double auction model is proposed to extend the battery life of cell-edge NB-IoT users (CENUs), supported by the EENU-MWM algorithm for efficient user matching. As IoT device usage grows, challenges such as spectrum congestion and limited hardware for continuous sensing arise. To address this, optimal sensing parameters and relay nodes are introduced in NB-CR-IoT and NB-CR-IoMT networks, improving throughput and reducing transmission power. In healthcare, real-time patient monitoring using IoT devices demands efficient spectrum usage and energy harvesting. A grouping-based design allows energy collection based on proximity to access points, enhancing performance in networks like Wireless Body Area Networks. Devices transmit data when the spectrum is unoccupied by primary users, maximizing energy use and lifespan while minimizing interference. This comprehensive approach ensures sustainable and scalable IoT communication across various sectors.
Intelligent Systems
Neural networks and fuzzy logic are two key areas of artificial intelligence that replicate aspects of human cognition. Neural networks are inspired by the brain's structure, consisting of interconnected neurons that process and learn from data. They are capable of supervised, unsupervised, and reinforcement learning, and are used in applications like pattern recognition, optimization, and speech processing. Key models include the perceptron, Hopfield networks, radial basis function networks, and Kohonen's self-organizing maps. Learning mechanisms involve weight adjustments based on input patterns and feedback. Fuzzy logic, on the other hand, deals with reasoning under uncertainty using fuzzy sets, linguistic variables, and membership functions. It contrasts with traditional binary logic by allowing partial truth values. Fuzzy systems use inference rules and defuzzification techniques to make decisions and are widely applied in control systems such as anti-lock braking systems (ABS) and industrial automation. Both paradigms are also being implemented in hardware, including VLSI, for faster and more efficient processing.
Multipath Minds
Video streaming has become a dominant form of digital content consumption, with user expectations for seamless, high-quality experiences steadily rising. This book presents a video streaming framework built on Multipath TCP (MPTCP) and Software Defined Networking (SDN) to enhance Quality of Experience (QoE). A key innovation is the use of a Genetic Algorithm (GA) to dynamically select optimal transmission paths based on bandwidth, latency, and link reliability, enabling adaptability in changing network conditions. Beyond path selection, the architecture incorporates service differentiation to prioritize video traffic and ensure fairness, along with durability enhancements to reduce playback interruptions. These combined mechanisms create an intelligent, adaptive system that delivers robust, high-quality video streaming across diverse network environments. The results show that this approach significantly improves user experience and meets service expectations across different user classes.
Emerging Technologies in Computing
This book LNICST 623 constitutes the refereed conference proceedings of the 7th International Conference on Emerging Technologies in Computing, iCETiC 2024, held in Essex, UK, during August 15-16, 2024. The 17 full papers were carefully reviewed and selected from 58 submissions. The proceedings focus on topics such as 1) AI, Expert Systems and Big Data Analytics 2) Cloud, IoT and Distributed Computing
Graph Machine Learning - Second Edition
Enhance your data science skills with this updated edition featuring new chapters on LLMs, temporal graphs, and updated examples with modern frameworks, including PyTorch Geometric, and DGLKey Features: - Master new graph ML techniques through updated examples using PyTorch Geometric and Deep Graph Library (DGL)- Explore GML frameworks and their main characteristics- Leverage LLMs for machine learning on graphs and learn about temporal learning- Purchase of the print or Kindle book includes a free PDF eBookBook Description: Graph Machine Learning, Second Edition builds on its predecessor's success, delivering the latest tools and techniques for this rapidly evolving field. From basic graph theory to advanced ML models, you'll learn how to represent data as graphs to uncover hidden patterns and relationships, with practical implementation emphasized through refreshed code examples. This thoroughly updated edition replaces outdated examples with modern alternatives such as PyTorch and DGL, available on GitHub to support enhanced learning.The book also introduces new chapters on large language models and temporal graph learning, along with deeper insights into modern graph ML frameworks. Rather than serving as a step-by-step tutorial, it focuses on equipping you with fundamental problem-solving approaches that remain valuable even as specific technologies evolve. You will have a clear framework for assessing and selecting the right tools.By the end of this book, you'll gain both a solid understanding of graph machine learning theory and the skills to apply it to real-world challenges.What You Will Learn: - Implement graph ML algorithms with examples in StellarGraph, PyTorch Geometric, and DGL- Apply graph analysis to dynamic datasets using temporal graph ML- Enhance NLP and text analytics with graph-based techniques- Solve complex real-world problems with graph machine learning- Build and scale graph-powered ML applications effectively- Deploy and scale your application seamlesslyWho this book is for: This book is for data scientists, ML professionals, and graph specialists looking to deepen their knowledge of graph data analysis or expand their machine learning toolkit. Prior knowledge of Python and basic machine learning principles is recommended.Table of Contents- Getting Started with Graphs- Graph Machine Learning- Neural Networks and Graphs- Unsupervised Graph Learning- Supervised Graph Learning- Solving Common Graph-Based Machine Learning Problems- Social Network Graphs- Text Analytics and Natural Language Processing Using Graphs- Graph Analysis for Credit Card Transactions- Building a Data-Driven Graph-Powered Application- Temporal Graph Machine Learning- GraphML and LLMs- Novel Trends on Graphs
Privacy Enhancing Techniques
This book provides a comprehensive exploration of advanced privacy-preserving methods, ensuring secure data processing across various domains. This book also delves into key technologies such as homomorphic encryption, secure multiparty computation, and differential privacy, discussing their theoretical foundations, implementation challenges, and real-world applications in cloud computing, blockchain, artificial intelligence, and healthcare. With the rapid growth of digital technologies, data privacy has become a critical concern for individuals, businesses, and governments. The chapters cover fundamental cryptographic principles and extend into applications in privacy-preserving data mining, secure machine learning, and privacy-aware social networks. By combining state-of-the-art techniques with practical case studies, this book serves as a valuable resource for those navigating the evolving landscape of data privacy and security. Designed to bridge theory and practice, this book is tailored for researchers and graduate students focused on this field. Industry professionals seeking an in-depth understanding of privacy-enhancing technologies will also want to purchase this book.
Cyber Warfare
China's INEW doctrine combining network attack with electronic warfare supports the use of cyber warfare in future conflict. The IW militia unit organization provides each Chinese military region commander with unique network attack, exploitation, and defense capabilities. IW unit training focuses on improving network attack skills during military exercises. The integration of the IW militia units with commercial technology companies provides infrastructure and technical support enabling the units to conduct operations. The IW units gather intelligence on an adversary's networks identifying critical nodes and security weaknesses. Armed with this intelligence, these units are capable of conducting network attack to disrupt or destroy the identified critical nodes of an enemy's C4ISR assets allowing China to use military force in a local war. In an effort to regain its former status, China pursues the strategic goal of reunification of its claimed sovereign territories and lands using economic influence as the primary means but will resort to military force if necessary. Recent cyber activities attributed to China suggest that network exploitation is currently underway and providing military, political, and economic information to the CCP. Domestically and internationally, China views Taiwan and the United States respectively as the major threats to the CCP.This work has been selected by scholars as being culturally important, and is part of the knowledge base of civilization as we know it. This work was reproduced from the original artifact, and remains as true to the original work as possible. Therefore, you will see the original copyright references, library stamps (as most of these works have been housed in our most important libraries around the world), and other notations in the work.This work is in the public domain in the United States of America, and possibly other nations. Within the United States, you may freely copy and distribute this work, as no entity (individual or corporate) has a copyright on the body of the work.As a reproduction of a historical artifact, this work may contain missing or blurred pages, poor pictures, errant marks, etc. Scholars believe, and we concur, that this work is important enough to be preserved, reproduced, and made generally available to the public. We appreciate your support of the preservation process, and thank you for being an important part of keeping this knowledge alive and relevant.
Cybermad
"Cyberspace has grown in importance to the United States (US), as well as the rest of the word. As such, the impact of cyberspace attacks have increased with time. Threats can be categorized as state or non-state actors. This research paper looks at state actors. It asks the question, should the US adopt a mutually assured destruction (MAD) doctrine for cyberspace? In order to answer this question, this research used a parallel historical case study. The case study was the US's nuclear MAD doctrine of the 1960s.This work has been selected by scholars as being culturally important, and is part of the knowledge base of civilization as we know it. This work was reproduced from the original artifact, and remains as true to the original work as possible. Therefore, you will see the original copyright references, library stamps (as most of these works have been housed in our most important libraries around the world), and other notations in the work.This work is in the public domain in the United States of America, and possibly other nations. Within the United States, you may freely copy and distribute this work, as no entity (individual or corporate) has a copyright on the body of the work.As a reproduction of a historical artifact, this work may contain missing or blurred pages, poor pictures, errant marks, etc. Scholars believe, and we concur, that this work is important enough to be preserved, reproduced, and made generally available to the public. We appreciate your support of the preservation process, and thank you for being an important part of keeping this knowledge alive and relevant.
Cyber Warfare
China's INEW doctrine combining network attack with electronic warfare supports the use of cyber warfare in future conflict. The IW militia unit organization provides each Chinese military region commander with unique network attack, exploitation, and defense capabilities. IW unit training focuses on improving network attack skills during military exercises. The integration of the IW militia units with commercial technology companies provides infrastructure and technical support enabling the units to conduct operations. The IW units gather intelligence on an adversary's networks identifying critical nodes and security weaknesses. Armed with this intelligence, these units are capable of conducting network attack to disrupt or destroy the identified critical nodes of an enemy's C4ISR assets allowing China to use military force in a local war. In an effort to regain its former status, China pursues the strategic goal of reunification of its claimed sovereign territories and lands using economic influence as the primary means but will resort to military force if necessary. Recent cyber activities attributed to China suggest that network exploitation is currently underway and providing military, political, and economic information to the CCP. Domestically and internationally, China views Taiwan and the United States respectively as the major threats to the CCP.This work has been selected by scholars as being culturally important, and is part of the knowledge base of civilization as we know it. This work was reproduced from the original artifact, and remains as true to the original work as possible. Therefore, you will see the original copyright references, library stamps (as most of these works have been housed in our most important libraries around the world), and other notations in the work.This work is in the public domain in the United States of America, and possibly other nations. Within the United States, you may freely copy and distribute this work, as no entity (individual or corporate) has a copyright on the body of the work.As a reproduction of a historical artifact, this work may contain missing or blurred pages, poor pictures, errant marks, etc. Scholars believe, and we concur, that this work is important enough to be preserved, reproduced, and made generally available to the public. We appreciate your support of the preservation process, and thank you for being an important part of keeping this knowledge alive and relevant.
Information Assurance and the Defense in Depth
This study investigates the Army's ability to provide information assurance for the NIPRNET. Information assurance includes those actions that protect and defend information and information systems by ensuring availability, integrity, authentication, confidentiality, and non-repudiation. The study examines how the military's defense in depth policy provides information assurance with a system of layered network defenses. The study also examines current practices used in the corporate world to provide information assurance. With the cooperation of the Human Firewall Council, the study compared the performance of four organizations according to standards developed for the Council's Security Management Index. The four participants in the study included: an Army Directorate of Information Management, a government agency, a university, and a web development company. The study also compared the performance of the four participants with the aggregate results obtained by the Human Firewall Council. The study concluded the defense in depth policy does grant the Army an advantage over other organizations for providing information assurance. However, the Army would benefit from incorporating some of the common practices of private corporations in their overall information assurance plans.This work has been selected by scholars as being culturally important, and is part of the knowledge base of civilization as we know it. This work was reproduced from the original artifact, and remains as true to the original work as possible. Therefore, you will see the original copyright references, library stamps (as most of these works have been housed in our most important libraries around the world), and other notations in the work.This work is in the public domain in the United States of America, and possibly other nations. Within the United States, you may freely copy and distribute this work, as no entity (individual or corporate) has a copyright on the body of the work.As a reproduction of a historical artifact, this work may contain missing or blurred pages, poor pictures, errant marks, etc. Scholars believe, and we concur, that this work is important enough to be preserved, reproduced, and made generally available to the public. We appreciate your support of the preservation process, and thank you for being an important part of keeping this knowledge alive and relevant.
Computer Security for ASSIST
This thesis examines the multilevel security problem of simultaneous processing of compartmented and collateral data at the Intelligence Data Handling Site, Forces Command Intelligence Group, Fort Bragg, North Carolina. Existing security controls are examined, and a list of software controls are discussed to reduce the risk of penetration, whether accidental or deliberate. Software controls are described in four major areas: access controls, input/output controls, residual controls, and audit trail controls. The security kernel is discussed as the heart of all software controls. A method of verifying the software is discussed and a procedure is explained for certifying the ASSIST system as possessing an acceptable security risk. Recommendations are described to reduce the risk of penetration and certify the system as secure through software controls.This work has been selected by scholars as being culturally important, and is part of the knowledge base of civilization as we know it. This work was reproduced from the original artifact, and remains as true to the original work as possible. Therefore, you will see the original copyright references, library stamps (as most of these works have been housed in our most important libraries around the world), and other notations in the work.This work is in the public domain in the United States of America, and possibly other nations. Within the United States, you may freely copy and distribute this work, as no entity (individual or corporate) has a copyright on the body of the work.As a reproduction of a historical artifact, this work may contain missing or blurred pages, poor pictures, errant marks, etc. Scholars believe, and we concur, that this work is important enough to be preserved, reproduced, and made generally available to the public. We appreciate your support of the preservation process, and thank you for being an important part of keeping this knowledge alive and relevant.
Computer Security for ASSIST
This thesis examines the multilevel security problem of simultaneous processing of compartmented and collateral data at the Intelligence Data Handling Site, Forces Command Intelligence Group, Fort Bragg, North Carolina. Existing security controls are examined, and a list of software controls are discussed to reduce the risk of penetration, whether accidental or deliberate. Software controls are described in four major areas: access controls, input/output controls, residual controls, and audit trail controls. The security kernel is discussed as the heart of all software controls. A method of verifying the software is discussed and a procedure is explained for certifying the ASSIST system as possessing an acceptable security risk. Recommendations are described to reduce the risk of penetration and certify the system as secure through software controls.This work has been selected by scholars as being culturally important, and is part of the knowledge base of civilization as we know it. This work was reproduced from the original artifact, and remains as true to the original work as possible. Therefore, you will see the original copyright references, library stamps (as most of these works have been housed in our most important libraries around the world), and other notations in the work.This work is in the public domain in the United States of America, and possibly other nations. Within the United States, you may freely copy and distribute this work, as no entity (individual or corporate) has a copyright on the body of the work.As a reproduction of a historical artifact, this work may contain missing or blurred pages, poor pictures, errant marks, etc. Scholars believe, and we concur, that this work is important enough to be preserved, reproduced, and made generally available to the public. We appreciate your support of the preservation process, and thank you for being an important part of keeping this knowledge alive and relevant.
Smart Grid and Internet of Things
This book constitutes the refereed proceedings of the 8th EAI International Conference on Smart Grid and Internet of Things, SGIoT 2024, held in Taichung, Taiwan, during November 23-24, 2024. The 19 full papers included in this book were carefully reviewed and selected from 45 submissions. They were organized in topical sections as follows: IoT, Artificial Intelligence, Edge Computing; Wireless Sensor Network, Mobile Robot, Smart Manufacturing; and Protocol, Algorithm, Services and Applications.
Information Assurance and the Defense in Depth
This study investigates the Army's ability to provide information assurance for the NIPRNET. Information assurance includes those actions that protect and defend information and information systems by ensuring availability, integrity, authentication, confidentiality, and non-repudiation. The study examines how the military's defense in depth policy provides information assurance with a system of layered network defenses. The study also examines current practices used in the corporate world to provide information assurance. With the cooperation of the Human Firewall Council, the study compared the performance of four organizations according to standards developed for the Council's Security Management Index. The four participants in the study included: an Army Directorate of Information Management, a government agency, a university, and a web development company. The study also compared the performance of the four participants with the aggregate results obtained by the Human Firewall Council. The study concluded the defense in depth policy does grant the Army an advantage over other organizations for providing information assurance. However, the Army would benefit from incorporating some of the common practices of private corporations in their overall information assurance plans.This work has been selected by scholars as being culturally important, and is part of the knowledge base of civilization as we know it. This work was reproduced from the original artifact, and remains as true to the original work as possible. Therefore, you will see the original copyright references, library stamps (as most of these works have been housed in our most important libraries around the world), and other notations in the work.This work is in the public domain in the United States of America, and possibly other nations. Within the United States, you may freely copy and distribute this work, as no entity (individual or corporate) has a copyright on the body of the work.As a reproduction of a historical artifact, this work may contain missing or blurred pages, poor pictures, errant marks, etc. Scholars believe, and we concur, that this work is important enough to be preserved, reproduced, and made generally available to the public. We appreciate your support of the preservation process, and thank you for being an important part of keeping this knowledge alive and relevant.
Web 3.0 Unleashed
Discover how the internet's next evolution is reshaping the world of business. The first of two volumes, Web 3.0 Unleashed: Transforming Experiences with AR, AI, and Immersive Technologies explores the groundbreaking technologies that define Web 3.0--blockchain, decentralized finance (DeFi), augmented reality, and artificial intelligence--and their profound impact on the way businesses innovate, grow, and connect with customers. Through insightful analysis and real-world examples, this contributed work provides a comprehensive guide to harnessing Web 3.0's potential. From revolutionising supply chains to reimagining customer engagement, every aspect of business is poised for transformation. Whether you're a technologist, entrepreneur, executive, academic, or student, this book equips you with the tools, strategies, and knowledge to thrive in the digital economy.
Progress in Cryptology - Africacrypt 2025
This book constitutes the refereed proceedings of the 16th International Conference on Cryptology in Africa, AFRICACRYPT 2025, which took place in Rabat, Morocco in July 2025. The 21 full papers presented in this volume were carefully reviewed and selected from 45 submissions. They are grouped into the following topics: Homomorphic Encryption; Cryptanalysis of RSA; Cryptography Arithmetic; Side-channel Attacks; Designs; Cryptanalysis.
Moderator-topics
"Moderator-topics, Volume 16" delves into the crucial aspects of online community management and content moderation. This volume explores the challenges and strategies involved in maintaining constructive and safe online environments. From handling user disputes to implementing content policies, this book offers insights relevant to anyone involved in moderating online forums, social media platforms, or digital communities. An essential resource for moderators, community managers, and those interested in the dynamics of online interactions, "Moderator-topics" provides a comprehensive overview of the tools and techniques necessary for fostering healthy and productive online spaces. Explore real-world examples and practical advice on navigating the complexities of digital communication.This work has been selected by scholars as being culturally important, and is part of the knowledge base of civilization as we know it. This work was reproduced from the original artifact, and remains as true to the original work as possible. Therefore, you will see the original copyright references, library stamps (as most of these works have been housed in our most important libraries around the world), and other notations in the work.This work is in the public domain in the United States of America, and possibly other nations. Within the United States, you may freely copy and distribute this work, as no entity (individual or corporate) has a copyright on the body of the work.As a reproduction of a historical artifact, this work may contain missing or blurred pages, poor pictures, errant marks, etc. Scholars believe, and we concur, that this work is important enough to be preserved, reproduced, and made generally available to the public. We appreciate your support of the preservation process, and thank you for being an important part of keeping this knowledge alive and relevant.
Emerging Patterns in Cybersecurity
In a digital era where cyber threats are evolving faster than ever, understanding the complexities of cybersecurity is critical for professionals, leaders, and technology enthusiasts alike. Emerging Patterns in Cybersecurity: Trends, Threats, and Strategies for a Resilient Digital Future offers a comprehensive exploration of the modern cybersecurity landscape, equipping readers with the knowledge and practical tools needed to safeguard against emerging risks. Unlike traditional cybersecurity texts that focus only on fundamentals or isolated topics, this book integrates emerging technologies such as artificial intelligence, blockchain, and quantum computing with practical frameworks and real-world applications, ensuring readers are prepared for both current and future security challenges.Readers will gain insights into the latest trends shaping the field, including AI and machine learning in threat detection, blockchain's role in securing transactions and managing identities, and the profound implications of quantum computing on encryption and data protection. Through real-world case studies and success stories, the book demonstrates how leading organisations have navigated complex threats with innovative solutions. Each chapter combines technical depth with actionable insights, enabling readers to apply concepts directly to their projects, organisational security policies, and strategic decision-making. It also offers practical frameworks for incident response, governance, compliance, and resilience building to strengthen cybersecurity posture holistically.Written by leading experts with extensive industry and academic experience, the authors bring diverse perspectives, bridging cutting-edge research with practical implementation strategies for professionals across the globe. Covering the future of cybersecurity with predictive analytics, evolving threat landscapes, and emerging technologies, this book equips readers not just to respond to threats but to anticipate them proactively.Whether you are a cybersecurity professional aiming to deepen your expertise, an IT leader seeking strategic knowledge, a student aspiring to build a career in security, or a business decision-maker responsible for digital safety, Emerging Patterns in Cybersecurity will empower you to make informed decisions and build robust defences for your organisation and career.Equip yourself with the knowledge and confidence to safeguard your digital environment, drive strategic security initiatives, and become a trusted leader in the cybersecurity domain.
Models, Metaphors, and Intuition
My goal in this writing is to promote social consciousness and increase awareness and understanding of the "human condition" that we all share, and that ultimately binds us all in our future, and our fate. I endeavor to pursue that goal with a series of discussions on how we think, how we learn, and how we communicate against the backdrop of our own individual consciousness, and to do so in an accessible manner. These discussions will leverage similarities of the human brain to neural networks in computing and artificial intelligence - as it has become increasingly important recently to understand these concepts.
How Large Language Models Work
Learn how large language models like GPT and Gemini work under the hood in plain English. How Large Language Models Work translates years of expert research on Large Language Models into a readable, focused introduction to working with these amazing systems. It explains clearly how LLMs function, introduces the optimization techniques to fine-tune them, and shows how to create pipelines and processes to ensure your AI applications are efficient and error-free. In How Large Language Models Work you will learn how to: - Test and evaluate LLMs - Use human feedback, supervised fine-tuning, and Retrieval augmented generation (RAG) - Reducing the risk of bad outputs, high-stakes errors, and automation bias - Human-computer interaction systems - Combine LLMs with traditional ML Purchase of the print book includes a free eBook in PDF and ePub formats from Manning Publications. How Large Language Models Work is written by some of the best machine learning researchers at Booz Allen Hamilton, including researcher Stella Biderman, Director of AI/ML Research Drew Farris, and Director of Emerging AI Edward Raff. In clear and simple terms, these experts lay out the foundational concepts of LLMs, the technology's opportunities and limitations, and best practices for incorporating AI into your organization. About the book How Large Language Models Work is an introduction to LLMs that explores OpenAI's GPT models. The book takes you inside ChatGPT, showing how a prompt becomes text output. In clear, plain language, this illuminating book shows you when and why LLMs make errors, and how you can account for inaccuracies in your AI solutions. Once you know how LLMs work, you'll be ready to start exploring the bigger questions of AI, such as how LLMs "think" differently that humans, how to best design LLM-powered systems that work well with human operators, and what ethical, legal, and security issues can--and will--arise from AI automation. About the reader Includes examples in Python. No knowledge of ML or AI systems is required. About the author Edward Raff is a Director of Emerging AI at Booz Allen Hamilton, where he leads the machine learning research team. He has worked in healthcare, natural language processing, computer vision, and cyber security, among fundamental AI/ML research. The author of Inside Deep Learning, Dr. Raff has over 100 published research articles at the top artificial intelligence conferences. He is the author of the Java Statistical Analysis Tool library, a Senior Member of the Association for the Advancement of Artificial Intelligence, and twice chaired the Conference on Applied Machine Learning and Information Technology and the AI for Cyber Security workshop. Dr. Raff's work has been deployed and used by anti-virus companies all over the world. Drew Farris is a Director of AI/ML Research at Booz Allen Hamilton. He works with clients to build information retrieval, as well as machine learning and large scale data management systems, and has co-authored Booz Allen's Field Guide to Data Science, Machine Intelligence Primer and Manning Publications' Taming Text, the 2013 Jolt Award-winning book on computational text processing. He is a member of the Apache Software Foundation and has contributed to a number of open source projects including Apache Accumulo, Lucene, Mahout and Solr. Stella Biderman is a machine learning researcher at Booz Allen Hamilton and the executive director of the non-profit research center EleutherAI. She is a leading advocate for open source artificial intelligence and has trained many of the world's most powerful open source artificial intelligence algorithms. She has a master's degree in computer science from the Georgia Institute of Technology and degrees in Mathematics and Philosophy from the University of Chicago.
Hacking Tricks, Methods, and Offensive Strategies
Understanding how systems are secured and how they can be breached is critical for robust cybersecurity in an interconnected digital world. The book offers a clear, practical roadmap for mastering ethical hacking techniques, enabling you to identify and fix vulnerabilities before malicious actors can exploit them.This book guides you through the entire hacking lifecycle, starting with fundamental rules and engagement phases, then moving into extensive reconnaissance using public data, search engines, and social networks to gather intelligence. You will learn active network scanning for live systems, port identification, and vulnerability detection, along with advanced enumeration techniques like NetBIOS, SNMP, and DNS. It also proceeds to explain practical system, exploitation, covering password cracking, social engineering, and specialized tools. It also includes dedicated sections on Wi-Fi network hacks, followed by crucial post-exploitation strategies for maintaining access and meticulously covering your tracks to remain undetected.This book helps you to properly protect data and systems by means of obvious explanations, practical recipes, and an emphasis on offensive tactics. Perfect for novices or experienced professionals with a networking background, it is your go-to tool for mastering cybersecurity and keeping hackers at bay, because slowing them down is the name of the game.WHAT YOU WILL LEARN● Use Nmap to scan networks and spot vulnerabilities in a quick manner.● Crack passwords with tools like Hashcat and John.● Exploit systems using Metasploit to test your defenses. ● Secure Wi-Fi by hacking it with Aircrack-ng first.● Think like a hacker to predict and block attacks.● Learn maintaining system access by hiding tracks and creating backdoors.WHO THIS BOOK IS FORThis book is for IT administrators and security professionals aiming to master hacking techniques for improved cyber defenses. To fully engage with these strategies, you should be familiar with fundamental networking and hacking technology concepts.
