Fuzzy Based Spam Filtering

Emails have proliferated in our ever-increasing communication, collaboration and information sharing. Unfortunately, one of the main abuses lacking complete benefits of this service is email spam (or shortly spam). Spam can easily bewilder system because of its availability and duplication, deceiving solicitations to obtain private information. The research community has shown an increasing interest to set up, adapt, maintain and tune several spam filtering techniques for dealing with emails and identifying spam and exclude it automatically without the interference of the email user. The contribution of this paper is twofold. Firstly, to present how spam filtering methodology can be constructed based on the concept of fuzziness mean, particularly, fuzzy c-means (FCM) algorithm. Secondly, to show how can the performance of the proposed FCM spam filtering approach (coined hence after as FSF) be improved. Experimental results on corpora dataset point out the ability of the proposed FSF when compared with the known Naïve Bayes filtering technique.