Email classification for spam detection using string detection

ABSTRACT Nowadays, spammers change one or more characters of offensive words in their spam in order to foil content based filters. But the important thing to observe is that the spammers change the words in such a way that a human being can understand the meaning the words without any difficulty. That’s why one might wonder why his spam filter does not detect some emails as spam when he can clearly see that those are spam! Spammers do not make any drastic change in the words so that it can be easily recognized by humans. Based on the above mentioned observations, we developed a rule based hashtable technique that can match string those both look alike and sound alike, cannot be detected by conventional spam filters. E-mail content classification for spam control is proposed. It used the string matching or hash table Technique for improving the efficiency of the content based spam filter.The proposed system extract the base or stem of a misspelled or modified string, to detect spam emails. In previous also provides an Email archiving solution which classifies the E-mail relating to a person,family, corporation, association, community, or nation &showed some algorithm results to corroborate our claim. Keywords Spam, Filters, Bayesian, content based spam filter, Word Stemming, Email, Email archiving.