DocumentCode
249203
Title
A hybrid approach for spam filtering using support vector machine and artificial immune system
Author
Jain, Kunal ; Agrawal, Sanjay
Author_Institution
Dept. of CEA, Nat. Inst. of Tech. Teachers´ Training & Res., Bhopal, India
fYear
2014
fDate
19-20 Aug. 2014
Firstpage
5
Lastpage
9
Abstract
Internet is a very powerful tool for information sharing; it provides email, chat, and audio/video talk for communication. All these email are widely used for official and non official communication because it is freely available to users and it also provides file transfer up to some limit. Hence use of Email (Electronic mail) services increasing rapidly due to higher dependency of organizations and individuals. Whenever Emails are sent/received unnecessarily then it is known as spam mail (Unsolicited Bulk Email). Spam Email is major issue for internet community because it causes wastage of resources and also pollutes our environment. Hence spam filtering is essential task. There are many existing techniques and algorithms available which focuses on individual parameters of the malicious content. Many times effectiveness of filtering algorithm gets significantly decreased, whenever spammer attacks on limitations of individual filtering mechanism. In this paper we have introduced an approach which includes advantages of Support Vector Machine and Artificial Immune System. In this approach we are trying to combine various positive properties of these filtering techniques at different level by deploying them in a hybrid approach. We have also discussed shortcomings of traditional spam filtering techniques in comparison of our proposed work.
Keywords
Internet; artificial immune systems; information filtering; security of data; support vector machines; unsolicited e-mail; Internet; Internet community; artificial immune system; audio-video talk; email services; filtering algorithm; individual filtering mechanism; information sharing; malicious content; organizations; spam email; spam filtering; spammer attacks; support vector machine; Feature extraction; Filtering; Immune system; Postal services; Support vector machines; Unsolicited electronic mail; Bandwidth; Email (electronic mail); Legitimate; Spam; similarity coefficient;
fLanguage
English
Publisher
ieee
Conference_Titel
Networks & Soft Computing (ICNSC), 2014 First International Conference on
Conference_Location
Guntur
Print_ISBN
978-1-4799-3485-0
Type
conf
DOI
10.1109/CNSC.2014.6906699
Filename
6906699
Link To Document