Computer Science

Computer Science ›› 2023, Vol. 50 ›› Issue (8): 286-293.doi: 10.11896/jsjkx.230100082

• Information Security • Previous Articles     Next Articles

Study on Optimized Offloading for Data Security in Industrial Scene

WANG Biao1, WANG Da2, KE Ji1, MA Yuqing2, ZHANG Yipu1, WANG Changqing3, LI Aijun3   

  1. 1 School of Energy and Electrical Engineering,Chang'an University,Xi'an,710061,China
    2 School of Electronics and Control Engineering,Chang'an University,Xi'an,710061,China
    3 School of Automation,Northwestern Polytechnical University,Xi'an,710072,China
  • Received:2023-01-16 Revised:2023-04-23 Online:2023-08-15 Published:2023-08-02
  • About author:WANG Biao,born in 1969,Ph.D professor.His main research interests include analysis and optimization of complex networks and multi-agent control.
    KE Ji,born in 1982,Ph.D,lecturer.His main research interests include analysis and control of complex networks,edge computing,hybrid feedback control and energy management.
  • Supported by:
    Key Projects of Natural Science Basic Research Program of Shaanxi Province(2019JZL-06) and 2023 Key Research and Development Program of Shaanxi Province,China(2023-YBSF-285).

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Abstract: The problem of security offloading in data transmission in industrial scenarios has gained wide attention.This paper is the first to integrate security policy as a decision variable into the optimization problem.It applies computational offloading principles and differential evolutionary algorithms,and proposes a data security offloading algorithm.Firstly,mathematical modeling conducted for four computing modes of industrial field devices:local computing,local edge computing,cross-plant edge computing in this paper,and cloud computing,as well as data security,and a data security offloading model is constructed by integrating multi-level security policies,task offloading,and resource allocation.Then,the security-optimized offloading scheme is formed by designing the objective function of maximizing device satisfaction by considering the effects of time delay and security risk probability.Finally,for this optimization problem,a data security offloading algorithm based on an improved differential evolution stra-tegy is proposed to maximize the device satisfaction of the system while satisfying the optimal solution with the latency and secu-rity risk requirements.Compared with the GASORA,GSOJRA and DEDSTO-NS algorithms,the proposed algorithm enables the field devices to satisfy the delay and risk probability requirements.Furthermore,it improves the device satisfaction by 35% while guaranteeing data security.Simulation results confirm the effectiveness of the proposed method and have some realistic application value.

Key words: Security strategy, Data security offloads, Differential evolution, Security risk probability, Equipment satisfaction

CLC Number: 

  • TP393
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