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P2P干预式蠕虫传播仿真分析*
引用本文:冯朝胜,杨军,卿昱,秦志光.P2P干预式蠕虫传播仿真分析*[J].计算机应用研究,2012,29(1):297-300.
作者姓名:冯朝胜  杨军  卿昱  秦志光
作者单位:1. 四川师范大学可视化计算与虚拟现实四川省重点实验室,成都610101;四川师范大学计算科学学院,成都610101;中国电子科技集团公司第30研究所,成都610041;电子科技大学计算机科学与工程学院,成都610054
2. 四川师范大学可视化计算与虚拟现实四川省重点实验室,成都610101;四川师范大学计算科学学院,成都610101
3. 中国电子科技集团公司第30研究所,成都,610041
4. 电子科技大学计算机科学与工程学院,成都,610054
基金项目:国家自然科学基金资助项目(60873075);可视化计算与虚拟现实四川省重点实验室课题(J2010N05);四川省科技厅应用基础项目(2010JY0125);四川省教育厅重点课题(10ZA007,11ZB069);西南交通大学信息编码与传输四川省重点实验室开放研究基金课题(2010-05)
摘    要:对P2P干预式主动型蠕虫的传播机制进行了研究,指出其传播主要包括四个阶段:信息收集,攻击渗透、自我推进与干预激活。研究发现,P2P干预式蠕虫实际是一种拓扑蠕虫,能利用邻居节点信息准确地确定攻击目标,而且攻击非常隐蔽。采用仿真的方法研究了P2P相关参数对P2P干预式蠕虫传播的影响。仿真实验表明,潜伏主机激活率对干预式蠕虫传播的影响最大,而攻击率对干预式蠕虫传播的影响较小。

关 键 词:主动型蠕虫  干预式蠕虫  P2P网络  仿真

Simulation and analysis on propagation of man activated worms in P2P network
FENG Chao-sheng,YANG Jun,QING Yu,QIN Zhi-guang.Simulation and analysis on propagation of man activated worms in P2P network[J].Application Research of Computers,2012,29(1):297-300.
Authors:FENG Chao-sheng  YANG Jun  QING Yu  QIN Zhi-guang
Affiliation:1.a.Visual Computing & Virtual Reality Key Laboratory of Sichuan Province,b.School of Computer Science,Sichuan Normal University,Chengdu 610101,China;2.The No.30 Institute of China Electronic Technology Corporation,Chengdu 610041,China;3.School of Computer Science & Engineering,University of Electronic Science & Technology of China,Chengdu 610054,China)
Abstract:This paper studied the propagation mechanism of the man-activating worm, which was a kind of active worms in the P2P network. The propagation procedure of this kind of worm consists of four stages: information collection, penetration, self propulsion and activating. It was found that the worm was a kind of topology-awareness worms. It could properly identify the patent target by exploiting the neighbor information, which was stored in its cache. This may made it very difficult to detect it. For the purpose of examining the effect of P2P-related parameters on propagation of the worm, developed simulation program. Simulations experiments show that amongst all the P2P-related parameters, the probability of worm being activated rather than the attacking rate has the most effect on worm propagation.
Keywords:active worms  man-activating worms  P2P networks  simulation
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