Proliferation and Detection of Blog Spam

Author

Abu-Nimeh, Saeed ; Chen, Thomas M.

Author_Institution

Websense, San Diego, CA, USA

Volume

8

Issue

5

fYear

2010

Firstpage

42

Lastpage

47

Abstract

The ease of posting comments and links in blogs has attracted spammers as an alternative venue to conventional email. An experimental study investigates the nature and prevalence of blog spam. Using Defensio logs, the authors collected and analyzed more than one million blog comments during the last two weeks of June 2009. They used a support vector machine (SVM) classifier combined with heuristics to identify spam posters´ IP addresses, autonomous system numbers (ASN), and IP blocks. Experimental results show that more than 75 percent of blog comments during the reporting period are spam. In addition, the results show that blog spammers likely operate from a few colocation facilities.

Keywords

Web sites; pattern classification; support vector machines; unsolicited e-mail; Defensio logs; IP blocks; autonomous system numbers; blog spam detection; blog spam proliferation; spam posters IP addresses; support vector machine classifier; Blogs; IP networks; Information services; Internet; Social network services; Support vector machines; Unsolicited electronic mail; Web sites; Web browser.; network-level security and protection;

fLanguage

English

Journal_Title

Security & Privacy, IEEE

Publisher

ieee

ISSN

1540-7993

Type

jour

DOI

10.1109/MSP.2010.113

Filename

5601487