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SAC
2009
ACM
14 years 10 days ago
Spam decisions on gray e-mail using personalized ontologies
E-mail is one of the most common communication methods among people on the Internet. However, the increase of e-mail misuse/abuse has resulted in an increasing volume of spam e-ma...
Seongwook Youn, Dennis McLeod
CEAS
2007
Springer
13 years 11 months ago
Learning Fast Classifiers for Image Spam
Recently, spammers have proliferated "image spam", emails which contain the text of the spam message in a human readable image instead of the message body, making detect...
Mark Dredze, Reuven Gevaryahu, Ari Elias-Bachrach
21
Voted
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...
ECIR
2006
Springer
13 years 9 months ago
Filtering Obfuscated Email Spam by means of Phonetic String Matching
Rule-based email filters mainly rely on the occurrence of critical words to classify spam messages. However, perceptive obfuscation techniques can be used to elude exact pattern ma...
Valerio Freschi, Andrea Seraghiti, Alessandro Bogl...
AI
2010
Springer
14 years 14 days ago
A Three-Way Decision Approach to Email Spam Filtering
Many classification techniques used for identifying spam emails, treat spam filtering as a binary classification problem. That is, the incoming email is either spam or non-spam....
Bing Zhou, Yiyu Yao, Jigang Luo