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Stochastic Differential Game-Based Malware Propagation in Edge Computing-Based IoT
Author(s) -
Li Miao,
Shuai Li
Publication year - 2021
Publication title -
security and communication networks
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.446
H-Index - 43
eISSN - 1939-0114
pISSN - 1939-0122
DOI - 10.1155/2021/8896715
Subject(s) - computer science , malware , enhanced data rates for gsm evolution , differential game , nash equilibrium , construct (python library) , internet of things , edge computing , computer security , distributed computing , mathematical optimization , artificial intelligence , computer network , mathematics
Internet of *ings (IoT) has played an important role in our daily life since its emergence. *e applications of IoTcover from the traditional devices to intelligent equipment. With the great potential of IoT, there comes various kinds of security problems. In this paper, we study the malware propagation under the dynamic interaction between the attackers and defenders in edge computing-based IoTand propose an infinite-horizon stochastic differential game model to discuss the optimal strategies for the attackers and defenders. Considering the effect of stochastic fluctuations in the edge network on the malware propagation, we construct the Itô stochastic differential equations to describe the propagation of the malware in edge computing-based IoT. Subsequently, we analyze the feedback Nash equilibrium solutions for our proposed game model, which can be considered as the optimal strategies for the defenders and attackers. Finally, numerical simulations show the effectiveness of our proposed game model.

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