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dc.contributor.authorCho, Jin-Hee
dc.contributor.authorGao, Jianxi
dc.date.accessioned2019-01-16T13:47:38Z
dc.date.available2019-01-16T13:47:38Z
dc.date.issued2016-02-09
dc.identifier.urihttp://hdl.handle.net/10919/86727
dc.description.abstractIn a cyber war game where a network is fully distributed and characterized by resource constraints and high dynamics, attackers or defenders often face a situation that may require optimal strategies to win the game with minimum effort. Given the system goal states of attackers and defenders, we study what strategies attackers or defenders can take to reach their respective system goal state (i.e., winning system state) with minimum resource consumption. However, due to the dynamics of a network caused by a node’s mobility, failure or its resource depletion over time or action(s), this optimization problem becomes NP-complete. We propose two heuristic strategies in a greedy manner based on a node’s two characteristics: resource level and influence based on k-hop reachability. We analyze complexity and optimality of each algorithm compared to optimal solutions for a small-scale static network. Further, we conduct a comprehensive experimental study for a large-scale temporal network to investigate best strategies, given a different environmental setting of network temporality and density. We demonstrate the performance of each strategy under various scenarios of attacker/defender strategies in terms of win probability, resource consumption, and system vulnerability.en_US
dc.description.sponsorshipResearch was, in part, for Dr. Jianxi Gao, sponsored by the Army Research Laboratory via the Network Science Collaborative Technology Alliance (NS CTA) program and was accomplished under Cooperative Agreement Number W911NF-09-2-0053. The views and conclusions contained in this document are those of the authors and should not be interpreted as representing the official policies, either expressed or implied, of the Army Research Laboratory or the U.S. Government. Dr. Jianxi Gao also acknowledges the support of the John Templeton Foundation: Mathematical and Physical Sciences grant number PFI-777; The Defense Threat Reduction Agency Basic Research Grant No. HDTRA1-10-1-0100; European Commission grant numbers FP7317532 (MULTIPLEX) and 641191 (CIMPLEX); and the National Natural Science Foundation of China (Grants 61374160 and 71201132). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.en_US
dc.language.isoen_USen_US
dc.publisherPLOSen_US
dc.rightsCC0 1.0 Universal*
dc.rights.urihttp://creativecommons.org/publicdomain/zero/1.0/*
dc.titleCyber War Game in Temporal Networksen_US
dc.typeArticle - Refereeden_US
dc.title.serialPLOS ONEen_US
dc.identifier.doihttps://doi.org/10.1371/journal.pone.0148674
dc.identifier.volume11en_US
dc.identifier.issue2en_US


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