Title :
Proliferation and Detection of Blog Spam
Author :
Abu-Nimeh, Saeed ; Chen, Thomas M.
Author_Institution :
Websense, San Diego, CA, USA
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;
Journal_Title :
Security & Privacy, IEEE
DOI :
10.1109/MSP.2010.113
