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P2P僵尸网络的传播建模与分析(2)

时间:2015-04-23 10:32 文章来源:http://www.lunwenbuluo.com 作者:冯丽萍等 点击次数:

  在任意时刻,网络中任一节点处于这4种状态中其中一种,并且在僵尸程序以及反病毒程序的作用下,随时间在这4种状态之间进行转化,具体转化过程如图1所示。 

  图6反映了感染率对僵尸网络传播规模有很大影响,当κ取0时,感染率是一常数(初始感染率β0),κ的值越大,感染率越小,僵尸网络传播的最终规模也越小。因此,降低感染率是有效控制僵尸网络传播规模的一个有效办法。实际网络管理中,可以通过不均匀分布易感染节点、断开已感染节点、安装反病毒软件等方法实现感染率的降低。 

  4 结语 

  P2P僵尸网络的大规模传播已经对网络安全造成了严重影响。本文根据Leeching botnet的形成过程建立了一个新的动力学模型,通过定性的数学分析找出了消除僵尸网络的临界值——基本再生数,最后通过Matlab数值模拟验证了理论分析的正确性。模拟结果表明:1)时滞τ的大小与僵尸网络传播达到稳定状态所需时间是成正比的,但是τ的大小不影响僵尸网络最终规模的大小;2)节点从E状态转化为I状态的比例越大,僵尸网络最终达到的规模就越大。本文的结果可以为有效预防和消除僵尸网络的爆发提供良好的理论基础。今后收集真实数据验证并且不断完善该模型是进一步的工作。 

  参考文献: 

  [1]FENG L, HAN Q, WANG H,et al. Effective immune measure on P2P botnet [J]. Journal of Computer Applications, 2012, 32(9): 2617-2619.(冯丽萍,韩琦,王鸿斌,等.P2P僵尸网络的有效免疫措施[J].计算机应用,2012,32(9):2617-2619.)

  [2]JIANG J, ZHUGE J, DUAN H,et al. Research on botnet mechanisms and defenses [J]. Journal of Software, 2012, 23(1): 82-96.(江健,诸葛建伟,段海新,等.僵尸网络机理与防御技术[J]. 软件学报,2012,23(1): 82-96.) 

  [3]HOLZ T, STEINER M, DAHL F,et al. Measurements and mitigation of peer-to-peer botnets: a case study on storm worm [C]// Proceeding of the 1st Usenix Workshop on Large-Scale Exploits and Emergent Threats. Berkeley: USENIX Association, 2008: 1-9. 

  [4]YAN G, HA D T, EIDENBENZ S. AntBot: anti-pollution peer-to-peer botnets [J]. Computer Networks, 2011, 55(8): 1941-1956. 

  [5]KOLESNICHENKOA, REMKEA, de BOER PT,et al.Compari-son of the mean-field approach and simulation in a peer-to-peer botnet case study [C]// EPEW 2011: Proceedings of the 8th European Performance Engineering Workshop, LNCS 6977. Berlin: Springer, 2011: 133-147. 

  [6]van RUITENBEEK E, SANDERS W H. Modeling peer-to-peer botnets [C]// QEST08: Proceeding of the 5th International Conference on the Quantitative Evaluation of Systems. Piscataway: IEEE, 2008: 307-316. 

  [7]WANGP, SPARKSS, ZOUC. An advanced hybridpeer-to-peer botnet [J]. IEEE Transactions on Dependable and Secure Computing, 2010, 7(2): 113-127. 

  [8]KHOSROSHAHY M, ALI M K, QIU D. The SIC botnet lifecycle model: a step beyond traditional epidemiological models [J]. Computer Networks, 2013, 57(2): 404-421. 

  [9]ZHANG J, PERDISCI R, LEE W,et al. Building a scalable system for stealthy P2P-botnet detection [J]. IEEE Transactions on Information Forensics and Security, 2014, 9(1): 27-38. 

  [10]KHATTAK S, RAMEY N R, KHAN K R,et al. A taxonomy of botnet behavior, detection, and defense [J]. IEEE Communications Surveys & Tutorials, 2014, 16(2): 898-924. 

  [11]WANG P, ASLAM B, ZOU C. Peer-to-peer botnet: the next generation of botnet attacks [M]. Berlin: Springer, 2010: 335-350. 

  [12]FENG L, WANG H, HAN Q,et al. Modeling peer-peer botnet on scale-free network [J]. Abstract and Applied Analysis, 2014, 2014: 1-8. 

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