Network traffic monitoring based on mining frequent patterns | |
Fang, Guodong ; Deng, Zhihong ; Ma, Hao | |
2009 | |
英文摘要 | To keep the network secure, it is necessary to monitor network traffic timely and effectively. The traditional methods for detecting network anomalies were mainly based on such ways as sampling, counting and aggregating, but they can not solve the problem of getting accurate and effective results well. In this paper we propose a new method that is based on the basic properties of frequent pattern mining problem and makes use of the vertical mining methods to mine frequent patterns from network traffic. Based on this algorithm, we build a prototype system to evaluate our algorithm on huge netflow data of campus network. The experimental result shows that this algorithm can detect network anomalies timely and effectively and can help network administrators achieve more effective monitoring on network. ? 2009 IEEE.; EI; 0 |
语种 | 英语 |
DOI标识 | 10.1109/FSKD.2009.444 |
内容类型 | 其他 |
源URL | [http://ir.pku.edu.cn/handle/20.500.11897/263106] ![]() |
专题 | 信息科学技术学院 |
推荐引用方式 GB/T 7714 | Fang, Guodong,Deng, Zhihong,Ma, Hao. Network traffic monitoring based on mining frequent patterns. 2009-01-01. |
个性服务 |
查看访问统计 |
相关权益政策 |
暂无数据 |
收藏/分享 |
除非特别说明,本系统中所有内容都受版权保护,并保留所有权利。
修改评论