论文部分内容阅读
现有的信息网络攻击与防御方面的研究主要集中于基于节点度的中枢点攻击与基于介数的攻击。Email网络反映人与人之间通过邮件通信所体现的社会关系。在模拟网络集、已知模块结构的真实网络和真实Email网络上做仿真实验,实验结果表明该方法对网络数据表示方法非常好,在Email用户类的聚类方面可以达到比现有方法更高的分类率,并且能更好地反映Email网络的自相似性。
The existing research on information network attack and defense mainly focuses on node-based hub attacks and medium-based attacks. The Email network reflects the social relationships that people embody through email communications. The simulation experiments on real network with real network with known module structure and real Email network are done. The experimental results show that this method is very good for network data representation, and can achieve higher performance than existing methods in the clustering of email users Of the classification rate, and can better reflect the Email network self-similarity.