Email Image Spam Detection Using Fast Support Vector Machine and Fast Convergence Particle Swarm Optimization
T. Kumaresan1, P. Subramanian2, D. Stalin Alex3, M.I. Thariq Hussan4, B. Stalin5
1Dr. T. Kumaresan, Professor, Department of CSE, Sri Indu College of Engineering and Technology, Hyderabad (Telangana), India.
2Dr. P. Subramanian, Professor, Department of CSE, Sri Indu College of Engineering and Technology, Hyderabad (Telangana), India.
3Dr. D. Stalin Alex, Professor, Department of IT, Guru Nanak Institute of Technology, Hyderabad (Telangana), India.
4Dr. M.I. Thariq Hussan, Professor and Head, Department of IT, Guru Nanak Institutions Technical Campus, Hyderabad (Telangana), India.
5Dr. B. Stalin, Assistant Professor, Department of Mechanical Engineering, Anna University, Regional Campus Madurai (Tamil Nadu), India.
Manuscript received on 19 May 2019 | Revised Manuscript received on 05 June 2019 | Manuscript Published on 15 June 2019 | PP: 19-22 | Volume-8 Issue-1S2 May 2019 | Retrieval Number: A00050581S219/2019©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: Today’s internet scenario, spam email is a major problem of internet users. The spam field has two different types namely email text spam and image spam. Now a day’s email spam filters are available in market, but the filters are capable to detect the text based spam only. Spammers are using intelligent ways to bypass the spam filters like embedding the spam text in an image so that spam filters are not able to detect the image spam. This paper analyses the various attributes of image spam with the careful attention given with the existing system. The proposed method uses the fast convergence particle swarm optimization technique which uses the diversity location of each particle by presenting a new classifier. Experimental results show that proposed method has achieved better accuracy than the other existing methods.
Keywords: Image Spam Detection, Email Spam, Support Vector Machine (SVM), Standard Particle Swarm Optimization (PSO), Fast Convergence Particle Swarm Optimization (FCPSO).
Scope of the Article: Swarm Intelligence