DocumentCode
2346992
Title
Spam Mail Classification Using Combined Approach of Bayesian and Neural Network
Author
Manjusha, K. ; Kumar, Rakesh
Author_Institution
Comput. Sci. & Inf. Syst. Group, Birla Inst. of Technol. & Sci., Pilani, India
fYear
2010
fDate
26-28 Nov. 2010
Firstpage
145
Lastpage
149
Abstract
Unsolicited commercial e-mail (spam) has shocked economies world over and is threatening the productivity. In this paper, an attempt has been made to classify email spam by combining Bayesian network and neural network classification approach. The header information like sender details and origin IP etc. was analyzed by centered Bayesian network, whereas the content and subject of the email were separately analyzed to classify the e-mail by neural network as a classifier trained by genetic algorithm (GA).
Keywords
belief networks; genetic algorithms; neural nets; pattern classification; unsolicited e-mail; Bayesian network; genetic algorithm; neural network; spam mail classification; unsolicited bulk email; Centered Bayesian Network; Spam Filter;
fLanguage
English
Publisher
ieee
Conference_Titel
Computational Intelligence and Communication Networks (CICN), 2010 International Conference on
Conference_Location
Bhopal
Print_ISBN
978-1-4244-8653-3
Electronic_ISBN
978-0-7695-4254-6
Type
conf
DOI
10.1109/CICN.2010.39
Filename
5701953
Link To Document