网络空间实体信度演化模型及其仿真
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摘要
"伪造"已经成为一种常见的网络攻击方式。研究针对"伪造"攻击的防御措施具有重要意义。"伪造"攻击依赖网络对伪造信息的信(任)度。提出了两种"伪造"攻击方式,并分析了"伪造"攻击的三个必要条件;根据D-S证据理论,建立了网络空间实体对事件的信度模型,设计了面向态势感知共享的网络空间信度合成算法,研究了"伪造"导致的网络实体信度的演化;仿真分析了"伪造"在无尺度网络和小世界网络上的信度合成和演化,得到了网络空间中信度演化的三个结论。
Of all cyber-attacks, 'fabrication' which is aimed at impacting one's awareness is becoming the common means, so it is of great importance to explore ways so as to defend such attacks. An attack can success or not always rely on the entities' belief of certain events. In this paper, two different ways of 'fabrication' attack are put forward, and three essential conditions for 'fabrication' attack are analyzed. Second, a cyberspace belief model in terms of the Dempster-Shafer framework based on situation awareness theory is built to study the evolution of the cyber entities' belief under the 'fabrication' attack. In addition, an algorithm used to compound D-S belief values among entities in cyberspace is designed. At last, the combination and evolution of D-S belief are studied on the scale-free network and the small world network, three conclusions are proposed at last.
Of all cyber-attacks, 'fabrication' which is aimed at impacting one's awareness is becoming the common means, so it is of great importance to explore ways so as to defend such attacks. An attack can success or not always rely on the entities' belief of certain events. In this paper, two different ways of 'fabrication' attack are put forward, and three essential conditions for 'fabrication' attack are analyzed. Second, a cyberspace belief model in terms of the Dempster-Shafer framework based on situation awareness theory is built to study the evolution of the cyber entities' belief under the 'fabrication' attack. In addition, an algorithm used to compound D-S belief values among entities in cyberspace is designed. At last, the combination and evolution of D-S belief are studied on the scale-free network and the small world network, three conclusions are proposed at last.
引文
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[4]G Shafer.Comparing approximate reasoning and probabilistic reasoning using the Dempster-Shafer framework[J].International Journal of Approximate Reasoning(S0888-613X),2009,50(5):812-821.
[5]S Mckeever,J Ye,L Coyle,et al.Using Dempster-Shafer Theory of Evidence for Situation Inference[J].Lecture Notes in Computer Science(S0302-9743),2009,5741(1):149-161.
[6]Endsley M.Toward a Theory of Situation Awareness in Dynamic Systems[J].Human Factors(S0018-7208),1995,37(1):35-64.
[7]Endsley M R.Measurement of Situation Awareness in Dynamic Systems[J].Human Factors(S0018-7208),1995,37(1):65-84.
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[9]史忠植.人工智能[M].北京:机械工业出版社,2016:123-131.SHI Zhong-zhi.Artificial Intelligence[M].Beijing:China Machine Press,2016:123-131.
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[11]Yong Deng.Generalized evidence theory[J].Applied Intelligence,2015,43(3):530-543.
[12]Barabási A-L.Scale-free networks:a decade and beyond[J].Science(S0036-8075),2009,325(5939):412-413.
[13]M E J Newman.Models of the Small World[J].Journal of Statistical Physics(S0022-4715),2000,101(3):819-841.
[14]Réka Albert,Hawoong Jeong,Albert-LászlóBarabási.Error and attack tolerance of complex networks[J].Nature,2000,406(1):378-381.
[15]Jianxi Gao,Yang-Yu Liu,Raissa M D’Souza,et al.Target control of complex networks[J].Nature Communications(S2041-1723),2014,5415(5):1-8.