An Analysis of Biometric Technology as an Enabler to Information Assurance
A Study to Determine Damage Assessment Methods or Models on Air Force Networks
Development of a Methodology for Customizing Insider Threat Auditing on a Linux Operating System
Automated Analysis of ARM Binaries Using the Low-Level Virtual Machine Compiler Framework
Using Relational Schemata in a Computer Immune System to Detect Multiple-Packet Network Intrusions
An Application of Automated Theorem Provers to Computer System Security
Developing a Gualia-Based Multi-Agent Architecture for use in Malware Detection
Geographic Location of a Computer Node Examining a Time-to-Location Algorithm and Multiple Autonomous System Networks
Development of an Malicious Insider Composite Vulnerability Assessment Methodology
U.S. Policy Recommendation for Responding to Cyber Attacks Against the United States
Intelligent Systems with Applications in Communications, Computing and Iot
This book LNICST 621 constitutes the proceedings of the First EAI International Conference on Intelligent Systems with Applications in Communications, Computing and IoT, ICISCCI 2024, held in Hyderabad, India, during August 23-24, 2024. The 39 full papers were carefully reviewed and selected from 97 submissions. The proceedings focuses on the topics such as 1) Intelligent systems and Machine Learning Applications 2) Intelligent Systems with Applications in Communication Networks 3) Intelligent Systems in IoT
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.
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.
Next Generation Data Science and Blockchain Technology for Industry 5.0
A groundbreaking view of the industrial models of the future Industry 5.0 is an increasingly widespread term for the coming business paradigm, which will combine humans, robotics, and smart technology to create the industrial processes of the future. Technological innovations like smart factories, networked processes, data science, Blockchain, and more will be combined to revolutionize industry and drive innovation at an unprecedented pace. Innovation-minded knowledge workers will be increasingly forced to grapple with challenging questions in order to meet the demands, and exploit the opportunities, of this groundbreaking paradigm. Next Generation Data Science and Blockchain Technology for Industry 5.0 offers an overview of these most important questions, their early answers, and the most promising paths forward. Incorporating practical case studies grounded in real-world data, the book emphasizes a hands-on approach combining numerous analytical tools. With a broad view of the historical role of industrial revolutions and a cutting-edge grasp of the key technologies, this book is an indispensable window into the future of business. Next Generation Data Science and Blockchain Technology for Industry 5.0 readers will also find: Incorporation of tools including statistical analysis, machine learning, graph analysis, and more Detailed treatment of cutting-edge technologies like additive manufacture (3D printing), edge computing, and many others Self-assessment tools to facilitate understanding Next Generation Data Science and Blockchain Technology for Industry 5.0 is ideal for academics, researchers, and advanced students in Computer Science and Computer Technology, as well as professionals and researchers working in Data Science or any other area of industrial technology.
Computational Science and Its Applications - Iccsa 2025 Workshops
Computational Science and Its Applications - Iccsa 2025 Workshops
Artificial Intelligence in Image Processing
Artificial Intelligence in Image Processing: Concepts, Techniques, and Applications provides a comprehensive exploration of how AI revolutionizes the field of digital imaging. It starts by tracing the evolution of image processing from manual techniques to advanced AI-driven methods. The book introduces foundational concepts in both image processing and AI, and covers key techniques including CNNs, GANs, RNNs, transfer learning, and autoencoders. It addresses core applications such as classification, segmentation, enhancement, 3D imaging, and medical diagnostics. Real-world case studies across healthcare, industry, and surveillance illustrate practical deployments. Ethical considerations, technical challenges, and future trends-including edge computing, AR/VR integration, and human-AI collaboration-are also examined, making this book an essential guide for students, researchers, and professionals in the AI and imaging domains.
Military Operations in Cyberspace
In the book cyberspace capabilities, threats, and attacks are described. The principles of the cyberspace operations' missions, characteristics, design, and planning are presented. The cybersecurity organizations and forces are reported. The bases of the decision-making process, operations execution, and targeting in cyberspace are formulated. The principles of cyberspace operations support, synchronization, and assessment are outlined. The role of cybersecurity in Homeland, critical infrastructure protection, and other operations is depicted. The cybersecurity strategy, guidance, and policy in the U.S., NATO, the European Community, and the Republic of Moldova are shown.The book is recommended for civil and military specialists from academic, scientific, and application levels, for license, master's, and PhD degree students.
Computer Networks
The book computer Networks provides a comprehensive introduction to the concepts and principles of data communication and networking. It covers the fundamental components involved in data transmission, the various types of computer networks, and their architectures. The book introduces key protocols and standards and explains how data travels across different layers of the OSI and TCP/IP models. It explores physical transmission methods, error detection and correction techniques, switching methods, and multiple access strategies. It also delves into network layer functions such as routing and addressing, transport layer protocols like TCP and UDP, and application-level services including DNS, email, FTP, and web communication. Security mechanisms like PGP and SSH are also discussed. The book is structured to build foundational knowledge and is widely used in academic settings for undergraduate computer science and engineering courses.
Computational Science and Its Applications - Iccsa 2025 Workshops
