Performance Evaluation of Spam Filtering Using Bayesian Approach
Archana Sahu1, Amit Mishra2, Shiv Kumar Sahu3
1Archana Sahu, M.Tech. Scholar, Department of Information Technology, Technocrats Institute of Technology, Bhopal (M.P.), India.
2Amit Mishra, Asst. Professor, Department of Information Technology, Technocrats Institute of Technology, Bhopal (M.P.), India.
2Dr. Shiv K Sahu, Professor & Head, Department of Information Technology, Technocrats Institute of Technology, Bhopal (M.P.), India.
Manuscript received on 13 June 2016 | Revised Manuscript received on 20 June 2016 | Manuscript Published on 30 June 2016 | PP: 57-63 | Volume-5 Issue-5, June 2016 | Retrieval Number: E4605065516/16©BEIESP
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Spam filtering is the technique to find out spams. This field is important aspect of text classification. Spam filtering technique is used with email servers, and population of spam is usually more than genuine emails, this is why spam filtering has become important technique. Most of existing spams filtering techniques are unable to detect spam because spammers know how to make spam to reach the destined email account without being filtered. In such situation, naïve bayes spam filter is proved to be a great technique, because several aspects are there to improve the performance of spam filter. Hence, it is an important research field in detecting spams. In this dissertation, technique for spam detection and filtering has been proposed based on Naïve Bayes classification technique, which is the existing spam filtering technique. Some enhancements are made in making it adaptive to new kind of spams. In existing spam filtering techniques, static filtering technique has been used, but we proposed dynamic and enhanced filtering technique, which helps in fast and accurate spam detection. Regular training of classifier should be done, database of spam should be updated all the time, and also a particular word should not be always behaved as spam word or a genuine word. Experimental results show that proposed enhancements improves accuracy of spam filtering.
Keywords: Spam Filtering, Detecting, Field, Accuracy Proposed Enhancements, Classifier Regular, Proposed, Spam
Scope of the Article: Classification