Research of Spam Filtering System Based on LSA and SHA

Authors:
Jingtao Sun;Qiuyu Zhang;Zhanting Yuan;Wenhan Huang;Xiaowen Yan;Jianshe Dong
Affiliations:
College of Electrical and Information Engineering, Lanzhou University of Technology, Lanzhou, China 730050 and College of Computer and Communication, Lanzhou University of Technology, Lanzhou, Chi ...;College of Computer and Communication, Lanzhou University of Technology, Lanzhou, China 730050;College of Computer and Communication, Lanzhou University of Technology, Lanzhou, China 730050;Department of Computer science and technology, Shaanxi University of Technology, Hanzhong, China 723003;Shaanxi Xiyu Highway Corporation Ltd. Hancheng, Shaanxi, China 715400;College of Computer and Communication, Lanzhou University of Technology, Lanzhou, China 730050
Venue:
ISNN '08 Proceedings of the 5th international symposium on Neural Networks: Advances in Neural Networks, Part II
Year:
2008

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Abstract

Along with the widespread concern of spam problem, at present, there are spam filtering system nowadays about the problem of semantic imperfection and spam filter low effect in the multi-send spam. This paper proposes a model of spam filtering which based on latent semantic analysis (LSA) and message-digest algorithm 5 (SHA). Making use of the LSA marks the latent feature phrase in the spam, semantic analysis is led into the spam filtering technique; the "e-mail fingerprint" of multi-send spam is born with SHA on the LSA analytical foundation, the problem of filtering technique's low effect in the multi-send spam is resolved with this kind of method. We have designed a spam filtering system based on this model. Our designed system was evaluated with an optional dataset. The results obtained were compared with KNN algorithm filter experiment results show that system based on Latent Semantic Analysis and SHA performs KNN. The experiments show the expected results obtained, and the feasibility and advantage of the new spam filtering method is validated.