Application of Refined LSA and MD5 Algorithms in Spam Filtering

Abstract

The paper proposes a spam filtering method that uses integrated and refined Latent Semantic Analysis (LSA) and Message-Digest Algorithm 5 (MD5) algorithms to address a series of universal problems in spam filtering, including remarkably lowered filtering precision and notably unbalanced filtering efficiency as a result of lack of latent semantic analysis of mail contents. In introducing LSA, its weighting function is improved by integrating fuzzy membership to improve effectiveness of LSA in processing mail contents. On top of this, MD5 algorithm is used to generate “E-mail fingerprint”, thus enabling quick matching and realizing highly efficient and accurate processing of mass- mailing spam. The result of the simulation experiment testifies effectiveness of the method.