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SIGCOMM
2006
ACM
14 years 1 months ago
Understanding the network-level behavior of spammers
This paper studies the network-level behavior of spammers, including: IP address ranges that send the most spam, common spamming modes (e.g., BGP route hijacking, bots), how persi...
Anirudh Ramachandran, Nick Feamster
CCS
2007
ACM
14 years 1 months ago
Filtering spam with behavioral blacklisting
Spam filters often use the reputation of an IP address (or IP address range) to classify email senders. This approach worked well when most spam originated from senders with fix...
Anirudh Ramachandran, Nick Feamster, Santosh Vempa...
CIKM
2009
Springer
13 years 11 months ago
A co-classification framework for detecting web spam and spammers in social media web sites
Social media are becoming increasingly popular and have attracted considerable attention from spammers. Using a sample of more than ninety thousand known spam Web sites, we found ...
Feilong Chen, Pang-Ning Tan, Anil K. Jain
CIKM
2010
Springer
13 years 6 months ago
Detecting product review spammers using rating behaviors
This paper aims to detect users generating spam reviews or review spammers. We identify several characteristic behaviors of review spammers and model these behaviors so as to dete...
Ee-Peng Lim, Viet-An Nguyen, Nitin Jindal, Bing Li...
WWW
2010
ACM
14 years 2 months ago
The social honeypot project: protecting online communities from spammers
We present the conceptual framework of the Social Honeypot Project for uncovering social spammers who target online communities and initial empirical results from Twitter and MySp...
Kyumin Lee, James Caverlee, Steve Webb