Solving Cyber Alert Allocation Markov Games with Deep Reinforcement Learning-Reference-Cited by-同舟云学术

Solving Cyber Alert Allocation Markov Games with Deep Reinforcement Learning

Published:2019 Issue: Volume: Page:164-183
ISSN:0302-9743
Container-title:Lecture Notes in Computer Science
language:
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Author:

Dunstatter Noah^ORCID,Tahsini Alireza^ORCID,Guirguis Mina^ORCID,Tešić Jelena^ORCID

Publisher

Springer International Publishing

Link

http://link.springer.com/content/pdf/10.1007/978-3-030-32430-8_11

Reference26 articles.

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2. Brown, G.W.: Iterative solution of games by fictitious play. In: Koopmans, T.C. (ed.) Activity Analysis of Production and Allocation. Wiley, New York (1951)

3. Brown, M., Sinha, A., Schlenker, A., Tambe, M.: One size does not fit all: a game-theoretic approach for dynamically and effectively screening for threats. In: AAAI Conference on Artificial Intelligence (2016)

4. Dunstatter, N., Guirguis, M., Tahsini, A.: Allocating security analysts to cyber alerts using markov games. In: 2018 National Cyber Summit (NCS) (2018)

5. Ganesan, R., Jajodia, S., Cam, H.: Optimal scheduling of cybersecurity analysts for minimizing risk. ACM Trans. Intell. Syst. Technol. 8, 52 (2015)

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