Modeling DNS Activities Based on Probabilistic Latent Semantic Analysis

摘要：

Traditional Web usage mining techniques aim at discovering usage patterns from Web data at the page level, while little work is engaged in at some upper level. In this paper, we propose a novel approach to the characterization of Internet users preference and interests at the domain name level. By summarizing Internet users domain name access behaviors as the cooccurrences of users and targeting domain names, an aspect model is introduced to classify users and domain names into various groups according to their cooccurrences. Meanwhile, each group is characterized by extracting the property of characteristic users and domain names. Experimental results on real-world data sets show that our approach is effective in which some meaningful groups are identified. Thus, our approach could be used for detecting unusual behaviors on the Internet at the domain name level, which can alleviate the work of searching the joint space of users and domain names.

关键词： Domain Name System Probabilistic latent semantic analysis Co-occurrence

作者: Xuebiao Yuchi Xiaodong Lee Jian Jin Baoping Yan

作者单位: China Internet Network Information Center, Computer Network Information Center, Chinese Academy of S China Internet Network Information Center, Computer Network Information Center, Chinese Academy of S

会议类型: 国际会议

会议名称: 6th International Conference on Advanced Data Mining and Applications(第六届先进数据挖掘及应用国际会议 ADMA 2010)

会议地点: 重庆

会议语种:英文

页码: 290-301

在线出版日期: 2010-11-19（万方平台首次上网日期，不代表论文的发表时间）