Home > Papers

 
 
Attacker's Cluster in Web Log Mining
Lv Jingshan #,Wen Qiaoyan *,Liu Hong
Beijing University of Posts and Telecommunications, State Key Laboratory of Networking and Switching Technology, Beijing, 100876, China
*Correspondence author
#Submitted by
Subject:
Funding: This work is supported by NSFC （No.Grant Nos. 61272057, 61202434, 61170270, 61100203, 61003286, 61121061), the Fundamental Research Funds for the Central Universities）
Opened online: 4 March 2014
Accepted by: none
Citation: Lv Jingshan,Wen Qiaoyan,Liu Hong.Attacker's Cluster in Web Log Mining[OL]. [ 4 March 2014] http://en.paper.edu.cn/en_releasepaper/content/4586778
 
 
According to analysis of web server logs attack events and security holes will be found, meanwhile attackers will also be discovered on the basis of source IP ad-dresses. To analyze logs and condense so many events, in this paper, attacker's similarity methods and the clus-ter algorithm are presented. After the definition of cha-racteristic matrix and the feature vector, an attacker clustering algorithm is devised. Each attacker has an feature vector, because of this the similarity of each attacker can be computed, user's clustering will be done according to their similarity. In addition effectiveness of this proposed algorithm will be proved by experiments.
Keywords:web log; law of cosines;attacker's similarity;cluster algorithm
 
 
 

For this paper
  • ● PDF (0B)
  • ● Revision 0 　　
  • ● Print this paper
  • ● Recommend this paper to a friend
  • ● Add to my favorite list

    Saved Papers

    Please enter a name for this paper to be shown in your personalized Saved Papers list

Tags
Add yours

Related Papers

Statistics
PDF Downloaded 492
Bookmarked 0
Recommend 5
Comments Array
Submit your papers