Game Theory and Machine Learning for Cyber Security
Charles A. Kamhou, Christopher D. Kiekintveld, Fei Fang, Quanyan Zhu

Informasi Umum

Kode

23.21.338

Klasifikasi

658.478 - Computer security

Jenis

Buku - Elektronik (E-Book)

Subjek

Computer Networks-security Measures, Game Theory,

No. Rak

Dilihat

243 kali

Informasi Lainnya

Abstraksi

Move beyond the foundations of machine learning and game theory in cyber security to the latest research in this cutting-edge field

In Game Theory and Machine Learning for Cyber Security, a team of expert security researchers delivers a collection of central research contributions from both machine learning and game theory applicable to cybersecurity. The distinguished editors have included resources that address open research questions in game theory and machine learning applied to cyber security systems and examine the strengths and limitations of current game theoretic models for cyber security.

Readers will explore the vulnerabilities of traditional machine learning algorithms and how they can be mitigated in an adversarial machine learning approach. The book offers a comprehensive suite of solutions to a broad range of technical issues in applying game theory and machine learning to solve cyber security challenges.

Beginning with an introduction to foundational concepts in game theory, machine learning, cyber security, and cyber deception, the editors provide readers with resources that discuss the latest in hypergames, behavioral game theory, adversarial machine learning, generative adversarial networks, and multi-agent reinforcement learning.

Readers will also enjoy:

A thorough introduction to game theory for cyber deception, including scalable algorithms for identifying stealthy attackers in a game theoretic framework, honeypot allocation over attack graphs, and behavioral games for cyber deception An exploration of game theory for cyber security, including actionable game-theoretic adversarial intervention detection against persistent and advanced threats Practical discussions of adversarial machine learning for cyber security, including adversarial machine learning in 5G security and machine learning-driven fault injection in cyber-physical systems In-depth examinations of generative models for cyber security
Perfect for researchers, students, and experts in the fields of computer science and engineering, Game Theory and Machine Learning for Cyber Security is also an indispensable resource for industry professionals, military personnel, researchers, faculty, and students with an interest in cyber security.

Koleksi & Sirkulasi

Tersedia 1 dari total 1 Koleksi

Pengarang

Nama	Charles A. Kamhou, Christopher D. Kiekintveld, Fei Fang, Quanyan Zhu
Jenis	Perorangan
Penyunting
Penerjemah

Penerbit

Nama	Wiley-IEEE Press
Kota	New York
Tahun	2021

Sirkulasi

Harga sewa	IDR 0,00
Denda harian	IDR 0,00
Jenis	Non-Sirkulasi

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