Autonomous Cyber Resilience by Charles A. Kamhoua (.PDF)
File Size: 10 MB
Autonomous Cyber Resilience by Charles A. Kamhoua, Alexander Kott, Quanyan Zhu, Nandi O. Leslie
Requirements: .PDF reader, 10 MB | True PDF
Overview: Authoritative and highly comprehensive resource on the latest research and strategies to develop cyber resilience in any network system. Autonomous Cyber Resilience presents key research contributions in the fields of cyber resilience, resilient Machine Learning, and game theory for network security. It introduces basic concepts on resilience assessment framework, human robot teaming, zero-trust cyber resilience, the Stackelberg network game, and Adversarial Machine Learning. The book describes a comprehensive suite of solutions for a broad range of technical challenges in autonomous cyber resilience, examines network robustness, planning, learning, and self-adaptation in a dynamic and uncertain environment and provides a joint analysis of cyber resilience and Machine Learning resilience. The book gathers experts in this emerging area of research to share their latest contributions in federated learning, resilient deep neural networks, topological data analysis, and effective deployment of honeypots, with valuable insights on applying these new methods to address cyber autonomy, network intrusion detection, and NextG communication systems. Additional chapters summarize ongoing research topics in cyber security and point to open issues and future research challenges and opportunities for academia and industry. Providing an extensive set of techniques to meet a diverse array of obstacles in the field, Autonomous Cyber Resilience is essential reading for researchers, students, and experts in the fields of Computer Science and engineering, along with industry and military professionals involved in projects related to cybersecurity.
Genre: Non-Fiction > Tech & Devices
Free Download links: