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"Security and Privacy in Social Networks" brings to the forefront
innovative approaches for analyzing and enhancing the security and
privacy dimensions in online social networks, and is the first
comprehensive attempt dedicated entirely to this field. In order to
facilitate the transition of such methods from theory to mechanisms
designed and deployed in existing online social networking
services, the book aspires to create a common language between the
researchers and practitioners of this new area- spanning from the
theory of computational social sciences to conventional security
and network engineering.
This book offers a comprehensive analysis of the theory and tools
needed for the development of an efficient and robust
infrastructure for the design of collaborative patrolling unmanned
aerial vehicle (UAV) swarms, focusing on its applications for
tactical intelligence drones. It discusses frameworks for robustly
and near-optimally analyzing flocks of semi-autonomous vehicles
designed to efficiently perform the ongoing dynamic patrolling and
scanning of pre-defined "search regions". It discusses the
theoretical limitations of such systems, as well as the trade-offs
between the systems' various economic and operational parameters.
Current UAV systems rely mainly on human operators for the design
and adaptation of drones' flying routes. However, recent
technological advances have introduced new systems, comprised of a
small number of self-organizing vehicles, manually guided at the
swarm level by a human operator. With the growing complexity of
such man-supervised architectures, it is becoming increasingly
harder to guarantee a pre-defined level of performance. The use of
large scale swarms of UAVs as a combat and reconnaissance platform
therefore necessitates the development of an efficient optimization
mechanism of their utilization, specifically in the design and
maintenance of their patrolling routes. The book is intended for
researchers and engineers in the fields of swarms systems and
autonomous drones.
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