文献类型：期刊文献

英文题名：Differential Game-Based Strategies for Preventing Malware Propagation in Wireless Sensor Networks

作者：Shen, Shigen[1,2];Li, Hongjie[2];Han, Risheng[2];Vasilakos, Athanasios V.[3];Wang, Yihan[4,5];Cao, Qiying[4]

机构：[1]Shaoxing Univ, Coll Engn, Shaoxing 312000, Peoples R China;[2]Jiaxing Univ, Coll Math Phys & Informat Engn, Jiaxing 314001, Peoples R China;[3]Kuwait Univ, Dept Comp Sci, Safat 13060, Kuwait;[4]Donghua Univ, Coll Informat Sci & Technol, Shanghai 201620, Peoples R China;[5]Shanghai Univ Engn Sci, Coll Elect & Elect Engn, Shanghai 201620, Peoples R China

年份：2014

卷号：9

期号：11

起止页码：1962

外文期刊名：IEEE TRANSACTIONS ON INFORMATION FORENSICS AND SECURITY

收录：SCI-EXPANDED(收录号：WOS:000344541100002)、、EI(收录号：20144400146594)、Scopus(收录号：2-s2.0-84908240474)、WOS

基金：This work was supported in part by the National Natural Science Foundation of China under Grant 61272034 and in part by the Zhejiang Provincial Natural Science Foundation of China under Grant LY13F030012 and Grant LY13F020035. The associate editor coordinating the review of this manuscript and approving it for publication was Prof. Wanlei Zhou.

语种：英文

外文关键词：Differential game; epidemic theory; Malware propagation; wireless sensor networks

外文摘要：Wireless sensor networks (WSNs) are prone to propagating malware because of special characteristics of sensor nodes. Considering the fact that sensor nodes periodically enter sleep mode to save energy, we develop traditional epidemic theory and construct a malware propagation model consisting of seven states. We formulate differential equations to represent the dynamics between states. We view the decision-making problem between system and malware as an optimal control problem; therefore, we formulate a malware-defense differential game in which the system can dynamically choose its strategies to minimize the overall cost whereas the malware intelligently varies its strategies over time to maximize this cost. We prove the existence of the saddle-point in the game. Further, we attain optimal dynamic strategies for the system and malware, which are bang-bang controls that can be conveniently operated and are suitable for sensor nodes. Experiments identify factors that influence the propagation of malware. We also determine that optimal dynamic strategies can reduce the overall cost to a certain extent and can suppress the malware propagation. These results support a theoretical foundation to limit malware in WSNs.