| 用关联方法推测网络蠕虫的传播路径 |
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| 引用本文： | 周建秋,石伟,李强. 用关联方法推测网络蠕虫的传播路径[J]. 吉林大学学报(理学版), 2009, 47(6): 1241-1245 |
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| 作者姓名： | 周建秋 石伟 李强 |
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| 作者单位： | 1. 吉林省血液中心, 长春 130061,2. 吉林大学 计算机科学与技术学院, 长春 130012 |
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| 基金项目： | 国家自然科学基金，吉林省科技发展计划项目基金 |
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| 摘 要： | 基于蠕虫病毒传播时其前后被感染节点在传播路径上存在着隐含的因果关系, 提出一种使用贝叶斯网络关联方法在线推测网络蠕虫传播路径的算法, 并通过模拟实验进行验证. 实验结果表明, 该算法较不采用关联的算法提高10%正确率, 更适合在线工作方式.
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| 关 键 词： | 蠕虫； 传播路径； 关联； 贝叶斯网络 |
| 收稿时间： | 2009-04-29 |
Tracing of Worm Propagation Path Correlation |
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| ZHOU Jian-qiu,SHI Wei,LI Qiang. Tracing of Worm Propagation Path Correlation[J]. Journal of Jilin University: Sci Ed, 2009, 47(6): 1241-1245 |
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| Authors: | ZHOU Jian-qiu SHI Wei LI Qiang |
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| Affiliation: | 1. Blood Center of Jilin Province, Changchun 130061, China;2. College of Computer Science and Technology, Jilin University, Changchun 130012, China |
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| Abstract: | Though worm is randomly spread, there exists implicit causality between adjacent infected nodes. Based on the analysis of causality, we presented an improved online tracing algorithm-Bayesian network correlation algorithm to acquire worm propagation path, and analyzed and verified its accuracy and performance through simulation experiments. Experiment result indicates that the detection accuracy of Bayesian network correlation algorithm has been increased by a factor of 10% compared to that of our previous work, this improved algorithm is more suitable for online detection. |
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| Keywords: | worm propagation path correlation Bayesian network |
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