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A differential game approach to patch injection

Yang, Luxing, Li, Pengdeng, Yang, Xiaofan, Xiang, Yong and Zhou, Wanlei 2018, A differential game approach to patch injection, IEEE access, vol. 6, doi: 10.1109/ACCESS.2018.2874446.

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Title A differential game approach to patch injection
Author(s) Yang, Luxing
Li, Pengdeng
Yang, Xiaofan
Xiang, YongORCID iD for Xiang, Yong orcid.org/0000-0002-1680-2521
Zhou, WanleiORCID iD for Zhou, Wanlei orcid.org/0000-0002-1680-2521
Journal name IEEE access
Volume number 6
Total pages 15
Publisher IEEE
Place of publication Piscataway, N.J.
Publication date 2018-10
ISSN 2169-3536
Summary To fight against evolving computer viruses, we must constantly inject new virus patches into computer networks. This paper addresses the patch injection problem, i.e., the problem of developing a patch injection strategy to mitigate the negative impact of virus attacks. As the impact of an attack depends on not only the patch injection strategy but the unknown virus injection strategy, the patch injection problem is very complicated. This paper initiates the study of the patch injection problem by means of security economics and differential game theory. First, based on a novel virus-patch mixed propagation model, we model the original problem as a differential game. Second, we develop a method for finding a candidate for the Nash equilibrium of the game, examine the structure of the candidate, and give some examples of the candidate. Next, we show through comparative experiments that the candidate is better in terms of the Nash equilibrium solution concept. Therefore, we recommend the patch injection strategy in the candidate. Finally, we examine the effects of some factors on the performance of the recommended patch injection strategy. Overall, these findings undoubtedly have guiding significance to defense against virus infections.
Language eng
DOI 10.1109/ACCESS.2018.2874446
HERDC Research category C1 Refereed article in a scholarly journal
Copyright notice ©2018, IEEE
Free to Read? Yes
Persistent URL http://hdl.handle.net/10536/DRO/DU:30114432

Document type: Journal Article
Collections: School of Information Technology
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