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Issue title: Special Section: Applied Machine Learning and Management of Volatility, Uncertainty, Complexity & Ambiguity (V.U.C.A)
Guest editors: Srikanta Patnaik
Article type: Research Article
Authors: Sun, Yan | Li, Yaobing | Chen, Xuehong | Li, Jun*;
Affiliations: China Industrial Control Systems Cyber Emergency Response Team, Beijing, China
Correspondence: [*] Corresponding author. Jun Li, China Industrial Control Systems Cyber Emergency Response Team, Beijing, China. E-mail: cic2019lijun@tom.com.
Abstract: Edge computing extends the cloud computing paradigm to the edge of the network to offset the shortcomings of traditional cloud computing in mobile support, low delay, and location awareness. However, traditional complicated encryption algorithms, access control measures, identification protocols, and privacy protection methods are inapplicable to security defense of edge computing given the multisource data fusion characteristics of edge computing, superposition of mobile and the Internet, and resource limitations in storage, computing, and battery capacity of edge terminals. Therefore, a reasonable defense model for complicated dynamic edge computing environment must be established. In accordance with the characteristics of limited resources of edge devices, combined with dynamic game theory, this study proposes an optimal defense strategy model based on a differential game and solves the optimal defense strategy of edge nodes in infinite and finite-horizons. The optimal defense strategy of the edge nodes was simulated under different conditions, and the simulation verifies that the edge nodes can obtain the optimal defense effect with minimum resource consumption when cooperating to form the defense system.
Keywords: Edge computing, differential game, defense strategy
DOI: 10.3233/JIFS-179919
Journal: Journal of Intelligent & Fuzzy Systems, vol. 39, no. 2, pp. 1449-1459, 2020
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