Improved Classifier Technique for Spam Filtering

Communication is primary need of human. SMS and email messages are one of such technique which is adoptable, efficient and cost effective. Now in these days most of the communications official and personal are performed using email messaging,But these mails are not much secure due to untrusted networks and intermediate network attackers. In our work the traditionally available techniques of spam filtering are investigated. Additionally a new technique using hybrid methodology which incorporates the Bayesian classifier and neural network is presented. Additionally the performance of the proposed technique is compared to the traditional Bayesian classifier. According to the obtained results the performance of the proposed classification technique is much adoptable than the traditional technique. Thus the proposed technique is high accurate and efficient than the traditionally available classification technique.