计算机科学

计算机科学 ›› 2023, Vol. 50 ›› Issue (8): 286-293.doi: 10.11896/jsjkx.230100082

• 信息安全 • 上一篇    下一篇

面向工业场景数据安全的优化卸载方法

王飚1, 王妲2, 柯吉1, 马雨庆2, 张懿璞1, 王长青3, 李爱军3   

  1. 1 长安大学能源与电气工程学院 西安 710061
    2 长安大学电子与控制工程学院 西安 710061
    3 西北工业大学自动化学院 西安 710072
  • 收稿日期:2023-01-16 修回日期:2023-04-23 出版日期:2023-08-15 发布日期:2023-08-02
  • 通讯作者: 柯吉(keji@chd.edu.cn)
  • 作者简介:(wangbiao@chd.edu.cn)
  • 基金资助:
    陕西省自然科学基础研究计划重点项目(2019JZL-06);陕西省2023年重点研发计划(2023-YBSF-285)

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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摘要： 针对工业场景数据传输过程中存在的安全卸载问题,文中首次将安全策略作为决策变量融入优化问题,应用计算卸载原理以及差分进化算法,提出了一种数据安全卸载算法。首先针对工业现场设备的本地计算、本地边缘计算、跨车间边缘计算和云计算4种计算模式以及数据安全进行数学建模,将多级安全策略、任务卸载和资源分配相融合,构建了数据安全卸载模型。综合考虑时延和安全风险概率的影响,设计最大化设备满意度的目标函数,形成了安全优化卸载方案。针对该优化问题,提出了一种基于改进的差分进化策略的数据安全卸载算法,在满足最优解的同时,在满足时延和安全风险的要求下实现系统的设备满意度最大化。相比GASORA算法、GSOJRA算法和DEDSTO-NS算法,所提算法不仅使现场设备满足了时延和风险概率的要求,并在保障数据安全性的同时,将设备满意度提高了35%。仿真结果证实了所提方法的有效性,且有一定的现实应用价值。

关键词: 安全策略, 数据安全卸载, 差分进化, 安全风险概率, 设备满意度

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

中图分类号: 

  • TP393
[1]TALEB T,SAMDANIS K,MADA B,et al.On multi-access edge computing:A survey of the emerging 5G network edge cloud architecture and orchestration[J].IEEE Communications Surveys and Tutorials,2017,19(3):1657-1681.
[2]YIN Y,CAO Z,XU Y,et al.QoS prediction for service recommendation with features learning in mobile edge computing environment[J].IEEE Transactions on Cognitive Communications and Networking,2020,6(4):1136-1145.
[3]FANG W,DING S,LI Y,et al.OKRA:Optimal task and re-source allocation for energy minimization in mobile edge computing systems[J].Wireless Networks,2019,25(5):2851-2867.
[4]ELGENDY I A,ZHANG W,TIAN Y C,et al.Resource allocation and computation offloading with data security for mobile edge computing[J].Future Generation Computer Systems,2019,100:531-541.
[5]ELGENDY I A,MUTHANNA A,HAMMOUDEH M,et al.Advanced deep learning for resource allocation and security aware data offloading in industrial mobile edge computing[J].Big Data,2021,9(4):265-278.
[6]SONG Y B,JIN X Y,YAN F,et al.Secure and energy-efficient offloading strategies for mobile edge computing in vehicular networking[J].Journal of Tsinghua University(Natural Science Edition),2021,61(11):1246-1253.
[7]JIANG X,SUN Y,LIU B,et al.Combinatorial double auctionfor resource allocation with differential privacy in edge computing[J].Computer Communications,2022,185:13-22.
[8]YAO Y,WANG Z,ZHOU P.Privacy-preserving and energy efficient task offloading for collaborative mobile computing in IoT:an ADMM approach[J].Computers and Security,2020,96:101886.
[9]ZHOU Y S,TAN C,TANG F.A multidimensional security query scheme for fog-enhanced industrial Internet of Things[J].Journal of Communication,2020,41(8):175-186.
[10]REN T Y,WANG X H,GUO G X,et al.Design of data security system for power IoT based on multi-level authentication and lightweight encryption[J].Journal of Nanjing University of Posts and Telecommunications(Natural Science Edition),2020,40(6):12-19.
[11]HE X L,REN Z Y,SHI C H,et al.Cloud-fog network for medi-cal big data and its distributed computing scheme[J].Journal of Xi'an Jiaotong University,2016,50(10):71-77.
[12]LI Z,CHANG V,HU H,et al.Profit maximization for security-aware task offloading in edge-cloud environment[J].Journal of Parallel and Distributed Computing,2021,157:43-55.
[13]ZHANG Y,LIU Y,ZHOU J,et al.Slow-movement particleswarm optimization algorithms for scheduling security-critical tasks in resource-limited mobile edge computing[J].Future Generation Computer Systems,2020,112:148-161.
[14]REN J,HE Y,YU G,et al.Joint communication and computation resource allocation for cloud-edge collaborative System[C]//2019 IEEE Wireless Communications and Networking Conference.2019:1-6.
[15]JIANG W,ZHANG X,MA Y.Energy aware real-time scheduling policy with guaranteed security protection[C]//19th Asia and South Pacific Design Automation Conference.2014:317-322.
[16]SINGHAL N,RAINA J.Comparative analysis of AES and RC4 algorithms for better utilization[J].International Journal of Computer Trends and Technology,2011,2(6):177-181.
[17]TRAD A,BAHATTAB A A,OTHMAN S B.Performance trade-offs of encryption algorithms for wireless sensor networks[C]//2014 World Congress on Computer Applications and Information Systems(WCCAIS).IEEE,2014:1-6.
[18]ALAM M,KHAN M.Performance and efficiency analysis ofdifferent block cipher algorithms of symmetric key cryptography[J].International Journal of Advanced Research in Computer Science and Software Engineering,2013,3(10):713-720.
[19]ZHU A,WEN Y.Computing offloading strategy using improved genetic algorithm in mobile edge computing system[J].Journal of Grid Computing,2021,19(3):38.
[20]SARVABHATLA M,KONDA S,VORUGUNTI C S,et al.A network aware energy efficient offloading algorithm for mobile cloud computing over 5G network[C]//2017 IEEE International Conference on Cloud Computing in Emerging Markets (CCEM).IEEE,2017:69-74.
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