Why attacking systems is a good idea, 2004. ,
Course of action generation for cyber security using classical planning Dynamic programming for POMDPs using a factored state representation, Proc. of ICAPS'05. Hansen, E., and Feng Proceedings of the International Conference on AI Planning and Scheduling (AIPS'00), 2000. ,
The Metric-FF planning system: Translating " ignoring delete lists " to numeric state variables, Journal of Artificial Intelligence Research, vol.20, pp.291-341, 2003. ,
Algorithm 447: efficient algorithms for graph manipulation, Communications of the ACM, vol.16, issue.6, pp.372-378, 1973. ,
DOI : 10.1145/362248.362272
Planning and acting in partially observable stochastic domains, Artificial Intelligence, vol.101, issue.1-2, pp.99-134, 1998. ,
DOI : 10.1016/S0004-3702(98)00023-X
SARSOP: Efficient Point-Based POMDP Planning by Approximating Optimally Reachable Belief Spaces, Robotics: Science and Systems IV, 2008. ,
DOI : 10.15607/RSS.2008.IV.009
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.149.450
Attack planning in the real world, Workshop on Intelligent Security, 2010. ,
State of the Art???A Survey of Partially Observable Markov Decision Processes: Theory, Models, and Algorithms, Management Science, vol.28, issue.1, pp.1-16, 1982. ,
DOI : 10.1287/mnsc.28.1.1
HTN-Style Planning in Relational POMDPs Using First-Order FSCs, Proceedings of the 34th German Conference on AI (KI'11), pp.216-227, 2011. ,
DOI : 10.1007/978-3-642-24455-1_20
Policycontingent abstraction for robust robot control, Proceedings of the 19th Conference on Uncertainty in Articifical Intelligence (UAI'03), pp.477-484, 2003. ,
Penetration testing == POMDP solving, Proceedings of the 3rd Workshop on Intelligent Security, 2011. ,
URL : https://hal.archives-ouvertes.fr/inria-00607403
An algorithm to find optimal attack paths in nondeterministic scenarios, Proceedings of the 4th ACM workshop on Security and artificial intelligence, AISec '11, 2011. ,
DOI : 10.1145/2046684.2046695