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Moving Target Defense II: Application of Game Theory and by Pratyusa K. Manadhata (auth.), Sushil Jajodia, Anup K.

By Pratyusa K. Manadhata (auth.), Sushil Jajodia, Anup K. Ghosh, V.S. Subrahmanian, Vipin Swarup, Cliff Wang, X. Sean Wang (eds.)

Our cyber defenses are static and are ruled via long procedures, e.g., for checking out and safeguard patch deployment. Adversaries might plan their assaults rigorously over the years and release assaults at cyber speeds at any given second. we'd like a brand new type of shielding thoughts that will strength adversaries to repeatedly have interaction in reconnaissance and re-planning in their cyber operations. One such method is to give adversaries with a relocating goal the place the assault floor of a process retains altering.

Moving objective safety II: program of online game concept and antagonistic Modeling includes contributions from global specialists within the cyber protection box. within the first quantity of MTD, we offered MTD ways in line with software program variations, and MTD ways in line with community and software program stack configurations. during this moment quantity of MTD, a gaggle of top researchers describe video game theoretic, cyber maneuver, and software program transformation techniques for developing and studying MTD structures.

Designed as a certified booklet for practitioners and researchers operating within the cyber defense box, complicated -level scholars and researchers all for machine technological know-how also will locate this e-book helpful as a secondary textual content ebook or reference.

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Both ticket sales and fines issued for fare evasion translate into revenue for the government. Therefore the optimization objective for the leader is to maximize total revenue (total ticket sales plus penalties). Urban transit systems, however, present unique computational challenges since there are exponentially many possible patrol strategies, each subject to both the spatial and temporal constraints of travel within the transit network under consideration. To overcome this challenge, TRUSTS uses a compact representation which captures 24 M.

One such area of great importance is securing urban city networks, transportation networks, computer networks and other network centric security domains. For example, after the terrorist attacks in Mumbai of 2008 [29] (refer Fig. 3), the Mumbai police have started setting up vehicular checkpoints on roads. We can model the problem faced by the Mumbai police as a security game between the Mumbai police and an attacker. In this urban security game, the pure strategies of the defender correspond to allocations of resources to edges in the network—for example, an allocation of police checkpoints to roads in the city.

Volume 3. North-Holland, Amsterdam (2002) 1947–1987 13. : Playing Games with Security: An Efficient Exact Algorithm for Bayesian Stackelberg Games. In: Proc. of The 7th International Conference on Autonomous Agents and Multiagent Systems (AAMAS). (2008) 895–902 14. : Computing the Optimal Strategy to Commit to. In: Proc. of the ACM Conference on Electronic Commerce (ACM-EC). (2006) 82–90 15. : Defending Critical Infrastructure. In: Interfaces. Volume 36. (2006) 530 – 544 16. : Computing Optimal Randomized Resource Allocations for Massive Security Games.

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