Filtering Spam Emails Based on User Behaviors

Mashael Alsowaiel, Omar Batarfi


Recently, more and more people are suffering from ever-increasing unwanted e-mails (named spam).It affects the cost of organizations and bothersome the email recipient. This paper will show an adaptive learning system that control spam emails by using user behaviour filtering. This filter can automatically adapt to the user interests, and it based on the action taken by the user by either delete or leaves the email. In addition to that the time taken for reading that email will be considered. This filter can recognize the meaning of each action has entered from the user and then it determines suspect rate for the filtered emails. Based on the rate that is given by the filter, the processed email will be considered either as spam or not. The results demonstrate that the technique has relatively lower false positives and false negatives. Also it is fast for adaptation to changing environment, show a good performance, and it is a good instant solution for spam filtering. So the users can reflect personality interest flow constantly by using this filter.




Keywords: spam email; Spam filter; Spam mail detection; behaviour recognition; user feedback, user action.

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