基于用户行为和网络拓扑的Email蠕虫传播

通过分析用户行为规律和电子邮件网络拓扑特征,提出了能够准确描述Email蠕虫传播特性的仿真算法。首先,基于Enron Email数据集构建了能够表征Email网络特点的仿真环境,实验结果验证了仿真算法能够准确地体现Email蠕虫传播特性。然后从理论和实验两方面分析验证了关键节点被感染后会加速蠕虫的传播的结论,并讨论了不同防护措施对蠕虫传播的抑制效果。最后建立了Email蠕虫传播数学解析模型(Topo-SIS),与仿真结果的比较表明,该模型能够较好地预测Email蠕虫的传播规模。

Email-worm propagation with user behavior and network topology

By introducing the effects of user behavior and network topology,a novel email-worm propagation simulation algorithm is presented.Also a practical simulation environment is established based on Enron-Email-Dataset for email-worm propagation simulation.Simulation results show that the proposed algorithm can describe the email-worm propagation behavior accurately.The impacts of network topology on email-worm propagation are analyzed and we found that the infected key-nodes can speed up the worm propagation.Also four protection strategies are proposed and examined through experiments.Results show that the imposed protections on key-node can slower the worm propagation.Furthermore,a new email-worm propagation model,named Topo-SIS,is built. Compared with the simulation results,this new model can predict the size of affected users accurately.