Modeling Spammer Behavior: Naïve Bayes vs. Artificial Neural Networks

Details Modeling Spammer Behavior: Naïve Bayes vs. Artificial Neural Networks Modeling Spammer Behavior: Naïve Bayes vs. Artificial Neural Networks

2010-08-19

arxiv.org/abs/1008.3282v1

Proc. of IEEE ICIMT, Jeju Island, South Korea, December 16-18, 2009, pp. 52-55

Computer Science

Information Retrieval

4 pages, 1 figure, 3 tables

Scientific paper

Addressing the problem of spam emails in the Internet, this paper presents a comparative study on Na\"ive Bayes and Artificial Neural Networks (ANN) based modeling of spammer behavior. Keyword-based spam email filtering techniques fall short to model spammer behavior as the spammer constantly changes tactics to circumvent these filters. The evasive tactics that the spammer uses are themselves patterns that can be modeled to combat spam. It has been observed that both Na\"ive Bayes and ANN are best suitable for modeling spammer common patterns. Experimental results demonstrate that both of them achieve a promising detection rate of around 92%, which is considerably an improvement of performance compared to the keyword-based contemporary filtering approaches.

Affiliated with

Also associated with

No associations

Rating

Modeling Spammer Behavior: Naïve Bayes vs. Artificial Neural Networks does not yet have a rating. At this time, there are no reviews or comments for this scientific paper.

If you have personal experience with Modeling Spammer Behavior: Naïve Bayes vs. Artificial Neural Networks, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Modeling Spammer Behavior: Naïve Bayes vs. Artificial Neural Networks will most certainly appreciate the feedback.

Rate now

Comments { 0 }

Profile ID: LFWR-SCP-O-135021