计算机科学 ›› 2024, Vol. 51 ›› Issue (11A): 231000005-6.doi: 10.11896/jsjkx.231000005
赵嘉, 谷良, 吴瑶, 杜锋
ZHAO Jia, GU Liang, WU Yao, DU Feng
摘要: 基于动态异构冗余框架的拟态防御技术是一种主动防御技术,其利用非相似性、冗余性等特征阻断或扰乱网络攻击,以提高系统的可靠性和安全性,其中最大化执行体之间的异构性是提高拟态防御安全效益的关键。文中提出了一种基于网络层次分析法(ANP)和误差反向传播(BP)的执行体异构性量化方法,该方法通过收集和分析不同的异构性影响因素,建立一个多维度的特征矩阵,利用ANP方法综合考虑了各个维度之间的相互依赖关系,对不同维度的特征进行权重分配,同时利用BP神经网络解决ANP方法带来的主观性过强的问题。通过基于ANP-BP的异构性评估模型,能够快速准确有效地筛选出影响异构性最大的因素,为拟态防御执行体异构性评估提供科学依据和技术建议。
中图分类号:
[1]WU J X.Research on mimicry defense in Cyberspace[J].Journal of Information Security,2016(4):1-10. [2]TONG Q,ZHANG Z,WU J X.Active defense technology based on software and hardware diversity[J].Journal of Information Security,2017,2(1):1-12. [3]YAO W B,YANG X Z.Different software component selection algorithm design[J].Journal of Harbin Institute of Technology,2003(3):261-264. [4]QIU D H,LI H,SUN J L.Measuring software similarity based on structure and property of class diagram[C]//Sixth International Conference on Advanced Computational Intelligence.IEEE,2013:75-80. [5]GAO M,LUO J,ZHOU H Y,et al.A differential feedbackscheduling decision algorithm based on mimicry defense[J].Telecommunication Science,2019,36(5):73-82. [6]LIU Q R,LIN S J,GU Z Y.Heterogeneous functional-equivalent block scheduling algorithm for mimicry security defense[J].Journal of Communications,2018,39(7):188-198. [7]TWU P,MOSTOFI Y,EGERSTEDT M.A measure of heterogeneity in multi-agent systems[C]//2014 American Control Conference.IEEE,2014:3972-3977. [8]YUE Y Y,FU X,DENG S.Multi-access edge Computing Server heterogeneity quantification Method based on mimicry defense[J].Computer Applications and Software,2019,40(6):276-281,349. [9]ZHANG J X,PANG J M,ZHANG Z,et al.A quantizationmethod for heterogeneity of network security systems based on dissimilar redundancy architecture[J].Journal of Electronics and Information Technology,2019,41(7):1594-1600. [10]ZHANG J X,PANG J M,ZHANG Z.A quantitative method for heterogeneity of Web servers based on mimicry construction[J].Journal of Software,2019,31(2):564-577. [11]LI J J.Research on Evaluation Method and Technology of mi-micry security information System[J].Information Technology and Network Security,2019,38(4):33-36. [12]WANG X M,YANG W H,ZHANG W,et al.Research onScheduling strategy of mimicry Web server based on BSG[J].Journal of Communications,2018,39(S2):112-120. [13]WU Z Q,WEI J.Heterogeneous executors scheduling algorithm for mimic defense systems[C]//2019 IEEE 2nd International Conference on Computer and Communication Engineering.Piscataway:IEEE Press,2019:279-284. [14]ZHANG Y J,YANG Y P,ZHOU Y,et al.State assessment of urban security development based on ANP-BP neural network[J].Journal of Xi 'an University of Science and Technology,2022,42(6):1104-1113. [15]LIU H.Research on Heterogeneous Software Deployment Stra-tegy for mimicry Defense System[D].Information Engineering University of Strategic Support Forces,2020. [16]WANG M,FU W H,WANG B T,et al.Optimization of mimicry defense strategy based on Evolutionary game [J].Application Research of Computers,2024,41(2):576-581. [17]JIANG D M,DING L.ANP-BP highway tunnel fire risk assessment model and its application[J].Journal of Qingdao University of Technology,2018,39(5):111-116. [18]WANG L F.Theory and Algorithm of Network Analysis Method(ANP)[J].Systems Engineering Theory & Practice,2001(3):44-50. [19]HUANG Y T,HUANG X B.BP neural network optimizationbased on ANP and Sparrow search algorithm for prefabricated building schedule risk assessment[J].Journal of Engineering Management,2019,36(6):36-41. |
|