This book offers a comprehensive exploration of federated learning (FL), a novel approach to decentralized, privacy-preserving machine learning. This book delves into the resilience and security challenges inherent to FL, such as model poisoning and malicious attacks, that jeopardize system integrity. Through cutting-edge research and practical insights, the book introduces defense mechanisms like representational similarity analysis and visual explanation techniques, which safeguard FL mo...

In-depth exploration of machine learning techniques applied to UAV operations and communications, highlighting areas of potential growth and research gapsArtificial Intelligence for Unmanned Aerial Vehicles provides a comprehensive overview of machine learning (ML) techniques used in unmanned aerial vehicle (UAV) operations, communications, sensing, and computing. It emphasizes key components of UAV activity to which ML can significantly contribute includi...

This book delves into the critical realm of trust management within the Internet of Vehicles (IOV) networks, exploring its multifaceted implications on safety and security which forms part of the intelligent transportation system domain.IoV emerges as a powerful convergence, seamlessly amalgamating the Internet of Things (IoT) and the intelligent transportation systems (ITS). This is crucial not only for safety-critical applications but is also an indispensable resource for non-saf...

In an era where vehicular networks and Location-Based Services (LBS) are rapidly expanding, safeguarding location privacy has become a critical challenge. Privacy in Vehicular Networks delves into the complexities of protecting sensitive location data within the dynamic and decentralized environment of vehicular networks. This book stands out by addressing both the theoretical and practical aspects of location privacy, offering a thorough analysis of existing vulnerabilities and i...

This comprehensive guide addresses key challenges at the intersection of data science, graph learning, and privacy preservation.It begins with foundational graph theory, covering essential definitions, concepts, and various types of graphs. The book bridges the gap between theory and application, equipping readers with the skills to translate theoretical knowledge into actionable solutions for complex problems. It includes practical insights into brain network analysis and the dyna...

Metal-Organic Framework Nanocomposites: From Design to Application assembles the latest advances in MOF nanocomposites, emphasizing their design, characterization, manufacturing, and application and offering a wide-ranging view of these materials with exceptional physical and chemical properties.FEATURESDiscusses various types of MOF materials, such as polyaniline MOF nanocomposites, magnetic MOF nanocomposites, and carbon nanotube-based MOF nanocom...