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Showing 1 - 3 of 3 matches in All Departments
Secure Broadcast Communication in Wired and Wireless Networks
presents a set of fundamental protocols for building secure
information distribution systems. Applications include wireless
broadcast, IP multicast, sensor networks and webs, ad hoc networks,
and satellite broadcast. This book presents and compares new
techniques for basic operations including: This book discusses how to realize these operations both with high performance processors and resource constrained processors. It shows how to protect against adversaries who inject packets or eavesdrop. The focus is on functional descriptions rather than theoretical discussions. Protocols are presented as basic building blocks that can be combined with each other and traditional security protocols. The book illustrates these protocols in practice by presenting a real implementation that provides security for an ad hoc sensor network. This book can serve as a textbook or supplementary reading in graduate level courses on security or networking, or can be used for self study.
Secure Broadcast Communication in Wired and Wireless Networks
presents a set of fundamental protocols for building secure
information distribution systems. Applications include wireless
broadcast, IP multicast, sensor networks and webs, ad hoc networks,
and satellite broadcast. This book presents and compares new
techniques for basic operations including: This book discusses how to realize these operations both with high performance processors and resource constrained processors. It shows how to protect against adversaries who inject packets or eavesdrop. The focus is on functional descriptions rather than theoretical discussions. Protocols are presented as basic building blocks that can be combined with each other and traditional security protocols. The book illustrates these protocols in practice by presenting a real implementation that provides security for an ad hoc sensor network. This book can serve as a textbook or supplementary reading in graduate level courses on security or networking, or can be used for self study.
Written by leading researchers, this complete introduction brings together all the theory and tools needed for building robust machine learning in adversarial environments. Discover how machine learning systems can adapt when an adversary actively poisons data to manipulate statistical inference, learn the latest practical techniques for investigating system security and performing robust data analysis, and gain insight into new approaches for designing effective countermeasures against the latest wave of cyber-attacks. Privacy-preserving mechanisms and the near-optimal evasion of classifiers are discussed in detail, and in-depth case studies on email spam and network security highlight successful attacks on traditional machine learning algorithms. Providing a thorough overview of the current state of the art in the field, and possible future directions, this groundbreaking work is essential reading for researchers, practitioners and students in computer security and machine learning, and those wanting to learn about the next stage of the cybersecurity arms race.
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