Title :
A Novel Online Spam Filter Based on URLs and Maximum Entropy Model
Author :
Li, Yang ; Fang, Bin-xing ; Li Guo
Author_Institution :
Inst. of Comput. Technol., Chinese Acad. of Sci., Beijing
Abstract :
Spam filtering is a great problem nowadays. The conventional spam filtering techniques still result in high false positives and false negatives. This paper proposes a novel online spam filter based on URLs and maximum entropy model. The filter identifies spam by classifying the e-mails with the pre-trained classifier based on the maximum entropy model and filters the spam online in terms of the characteristics of SMTP. Experimental results demonstrate it can significantly raise the filtering accuracy, effectively reduce false positives and can be applied to online processing environment by reducing the computational cost than the state-of-the-art techniques
Keywords :
Internet; information filtering; information filters; maximum entropy methods; pattern classification; security of data; unsolicited e-mail; Internet; e-mail classification; maximum entropy model; online spam filter; Computational efficiency; Computers; Electronic mail; Entropy; Information filtering; Information filters; Postal services; Support vector machines; Uniform resource locators; Unsolicited electronic mail;
Conference_Titel :
Computational Intelligence and Security, 2006 International Conference on
Conference_Location :
Guangzhou
Print_ISBN :
1-4244-0605-6
Electronic_ISBN :
1-4244-0605-6
DOI :
10.1109/ICCIAS.2006.295327