Game Theory and Machine Learning for Cyber Security
GAME THEORY AND MACHINE LEARNING FOR CYBER SECURITYMove beyond the foundations of machine learning and game theory in cyber security to the latest research in this cutting-edge fieldIn 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 secu…
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Produktdetails
Weitere Autoren: Zhu, Quanyan (Hrsg.) / Fang, Fei (Hrsg.) / Kiekintveld, Christopher D. (Hrsg.)
- ISBN: 978-1-119-72391-2
- EAN: 9781119723912
- Produktnummer: 37410747
- Verlag: Wiley
- Sprache: Englisch
- Erscheinungsjahr: 2021
- Seitenangabe: 544 S.
- Plattform: PDF
- Masse: 14'084 KB
Über den Autor
Charles A. Kamhoua, PhD, is a researcher at the United States Army Research Laboratory's Network Security Branch. He is co-editor of Assured Cloud Computing (2018) and Blockchain for Distributed Systems Security (2019), and Modeling and Design of Secure Internet of Things (2020). Christopher D. Kiekintveld, PhD, is Associate Professor at the University of Texas at El Paso. He is Director of Graduate Programs with the Computer Science Department. Fei Fang, PhD, is Assistant Professor in the Institute for Software Research at the School of Computer Science at Carnegie Mellon University. Quanyan Zhu, PhD, is Associate Professor in the Department of Electrical and Computer Engineering at New York University.
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