Fetching the paper…
Reading the bibliography…
The field of cybersecurity has mostly been a cat-and-mouse game with the discovery of new attacks leading the way.
Stochastic games
Lloyd S Shapley · 1953
Earlier work this paper cites.
Contributions to the Theory of Games
Harold William Kuhn and Albert William Tucker · 1953
Earlier work this paper cites.
On generalized stackelberg strategies
George Leitmann · 1978
Earlier work this paper cites.
Markov games as a framework for multi-agent reinforcement learning
Michael L Littman · 1994
Earlier work this paper cites.
Multiagent reinforcement learning: theoretical framework and an algorithm
Junling Hu, Michael P Wellman, et al · 1998
Earlier work this paper cites.
A unified analysis of value-function-based reinforcement-learning algorithms
Csaba Szepesvári and Michael L Littman · 1999
Earlier work this paper cites.
Friend-or-foe q-learning in general-sum games
Michael L Littman · 2001
Earlier work this paper cites.
Automated generation and analysis of attack graphs
Oleg Sheyner, Joshua Haines, Somesh Jha, Richard Lippmann, and Jeannette M Wing · 2002
Earlier work this paper cites.
Multi-agent reinforcement learning: a critical survey
Yoav Shoham, Rob Powers, and Trond Grenager · 2003
Earlier work this paper cites.
Correlated q-learning
Amy Greenwald, Keith Hall, and Roberto Serrano · 2003
Earlier work this paper cites.
Leadership with commitment to mixed strategies
BV Stengel and S Zamir · 2004
Earlier work this paper cites.
Asymmetric multiagent reinforcement learning
Ville Könönen · 2004
Earlier work this paper cites.
Bayesian games for threat prediction and situation analysis
Joel Brynielsson and Stefan Arnborg · 2004
Earlier work this paper cites.
Computing the optimal strategy to commit to
Vincent Conitzer and Tuomas Sandholm · 2006
Earlier work this paper cites.
Leader-follower semi-markov decision problems: theoretical framework and approximate solution
Kurian Tharakunnel and Siddhartha Bhattacharyya · 2007
Earlier work this paper cites.
Playing games for security: An efficient exact algorithm for solving bayesian stackelberg games
Praveen Paruchuri, Jonathan P Pearce, Janusz Marecki, Milind Tambe, Fernando Ordonez, and Sarit Kraus · 2008
Earlier work this paper cites.
Playing games for security: An efficient exact algorithm for solving bayesian stackelberg games
Praveen Paruchuri, Jonathan P Pearce, Janusz Marecki, Milind Tambe, Fernando Ordonez, and Sarit Kraus · 2008
Earlier work this paper cites.
Dynamic policy-based ids configuration
Quanyan Zhu and Tamer Başar · 2009
Cited alongside, same era.
Lecture notes on non-cooperative game theory
Tamer Basar et al · 2010
Cited alongside, same era.
Moving target defense: creating asymmetric uncertainty for cyber threats
Sushil Jajodia, Anup K Ghosh, Vipin Swarup, Cliff Wang, and X Sean Wang · 2011
Cited alongside, same era.
Markov games of incomplete information for multi-agent reinforcement learning
Liam MacDermed, Charles Isbell, and Lora Weiss · 2011
Cited alongside, same era.
Computing stackelberg equilibria in discounted stochastic games
Yevgeniy Vorobeychik and Satinder Singh · 2012
Cited alongside, same era.
Game-theoretic approach to feedback-driven multi-stage moving target defense
Quanyan Zhu and Tamer Başar · 2013
Cited alongside, same era.
Leader-follower mdp models with factored state space and many followers-followers abstraction, structured dynamics and state aggregation
Régis Sabbadin and Anne-France Viet · 2016
Later among the works it cites.
Moving target defense: a symbiotic framework for ai & security
Sailik Sengupta · 2017
Later among the works it cites.
A game theoretic approach to strategy generation for moving target defense in web applications
Sailik Sengupta, Satya Gautam Vadlamudi, Subbarao Kambhampati, Adam Doupé, Ziming Zhao, Marthony Taguinod, and Gail-Joon Ahn · 2017
Later among the works it cites.
On markov games played by bayesian and boundedly-rational players
Muthukumaran Chandrasekaran, Yingke Chen, and Prashant Doshi · 2017
Later among the works it cites.
A multi-agent reinforcement learning algorithm based on stackelberg game
Chi Cheng, Zhangqing Zhu, Bo Xin, and Chunlin Chen · 2017
Later among the works it cites.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Solving security games on graphs via marginal probabilities
Joshua Letchford and Vincent Conitzer · 2013
Cited alongside, same era.
Finite depth of reasoning and equilibrium play in games with incomplete information
Willemien Kets · 2013
Cited alongside, same era.
A game theoretic approach to strategy determination for dynamic platform defenses
Kevin M Carter, James F Riordan, and Hamed Okhravi · 2014
Cited alongside, same era.
Towards a theory of moving target defense
Rui Zhuang, Scott A DeLoach, and Xinming Ou · 2014
Cited alongside, same era.
From physical security to cybersecurity
Arunesh Sinha, Thanh H Nguyen, Debarun Kar, Matthew Brown, Milind Tambe, and Albert Xin Jiang · 2015
Cited alongside, same era.
Dynamic ids configuration in the presence of intruder type uncertainty
Xiaofan He, Huaiyu Dai, Peng Ning, and Rudra Dutta · 2015
Cited alongside, same era.
Ankur Chowdhary, Sailik Sengupta, Dijiang Huang, and Subbarao Kambhampati · 2018
Later among the works it cites.
An initial study of targeted personality models in the flipit game
Anjon Basak, Jakub Černỳ, Marcus Gutierrez, Shelby Curtis, Charles Kamhoua, Daniel Jones, Branislav Bošanskỳ, and Christopher Kiekintveld · 2018
Later among the works it cites.
Deceiving cyber adversaries: A game theoretic approach
Aaron Schlenker, Omkar Thakoor, Haifeng Xu, Fei Fang, Milind Tambe, Long Tran-Thanh, Phebe Vayanos, and Yevgeniy Vorobeychik · 2018
Later among the works it cites.
M 3 rl: Mind-aware multi-agent management reinforcement learning
Tianmin Shu and Yuandong Tian · 2018
Later among the works it cites.
Lisa Oakley and Alina Oprea · 2019
Later among the works it cites.
Deep reinforcement learning based adaptive moving target defense
Taha Eghtesad, Yevgeniy Vorobeychik, and Aron Laszka · 2019
Later among the works it cites.
General sum markov games for strategic detection of advanced persistent threats using moving target defense in cloud networks
Sailik Sengupta, Ankur Chowdhary, Dijiang Huang, and Subbarao Kambhampati · 2019
Later among the works it cites.
Learning expensive coordination: An event-based deep rl approach
Zhenyu Shi, Runsheng Yu, Xinrun Wang, Rundong Wang, Youzhi Zhang, Hanjiang Lai, and Bo An · 2019
Later among the works it cites.
A survey of moving target defenses for network security
Sailik Sengupta, Ankur Chowdhary, Abdulhakim Sabur, Adel Alshamrani, Dijiang Huang, and Subbarao Kambhampati · 2020
Closest in time.
Spatial-temporal moving target defense: A markov stackelberg game model
Henger Li, Wen Shen, and Zizhan Zheng · 2020
Closest in time.
https://nvd.nist.gov
National vulnerability database · 2020
Closest in time.