Restrain the Linkage to Malicious Web Pages though Negative Link Weight

被引:0
|
作者
Luo, Jiangfeng
Zhu, Cheng
Zhang, Weiming
Liu, Zhong
Huang, Jincai
机构
关键词
D O I
10.1109/KAM.2008.56
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Currently, the search engine is mainly based on the web content-identifying technique to deal with malicious web pages. As long as the malicious content is identified, it is common to simply filter out the malicious pages or give some security warnings. They don't distinguish the linkage to malicious pages from others during the page's rank. This paper mainly researches on the impact of the malicious web pages on user's surfing action and present a new surfing action model. Under the new surfing model, we put forward a new page rank algorithm with negative link weight penalty to restrain the linkage to malicious pages, in which the web pages which link to malicious pages are punished. Subsidiary nodes are introduced to ensure the correctness and effectiveness of the algorithm under different conditions. Both theoretic analysis and simulation result show authority values of the pages linking to malicious pages will be reduced It effectively restrains the linkage to malicious web pages from the perspective of link analysis.
引用
收藏
页码:262 / 267
页数:6
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