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Game Theory and Machine Learning for Cyber Security

Contributor(s): Kamhoua, Charles A (Editor), Kiekintveld, Christopher D (Editor), Fang, Fei (Editor), Zhu, Quanyan (Editor)

ISBN: 9781119723929

Publisher: Wiley-IEEE Press

Hardcover
$149.95
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Pub Date: September 15, 2021

Dewey: 658.478

LCCN: 2021031984

Lexile Code: 0000

Features: Bibliography, Index

Target Age Group: NA to NA

Physical Info: 1.40" H x 10.00" L x 6.90" W ( 2.45 lbs) 544 pages

Descriptions, Reviews, etc.

Description: "Cyber security is a serious concern to our economic prosperity and national security. Despite an increased investment in cyber defense, cyber-attackers are becoming more creative and sophisticated. This exposes the need for a more rigorous approach to cyber security, including methods from artificial intelligence including computational game theory and machine learning. Recent advances in adversarial machine learning are promising to make artificial intelligence (AI) algorithms more robust to deception and intelligent manipulation. However, they are still vulnerable to adversarial inputs, data poisoning, model stealing and evasion attacks. The above challenges and the high risk and consequence of cyber-attacks drive the need to accelerate basic research on cyber security"--

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