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» The Fight against Spam - A Machine Learning Approach
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COMPSEC
2006
132views more  COMPSEC 2006»
13 years 7 months ago
Tightening the net: A review of current and next generation spam filtering tools
This paper provides an overview of current and potential future spam filtering approaches. We examine the problems spam introduces, what spam is and how we can measure it. The pap...
James Carpinter, Ray Hunt
JMLR
2010
185views more  JMLR 2010»
13 years 2 months ago
HMMPayl: an application of HMM to the analysis of the HTTP Payload
Zero-days attacks are one of the most dangerous threats against computer networks. These, by definition, are attacks never seen before. Thus, defense tools based on a database of ...
Davide Ariu, Giorgio Giacinto
SIGIR
2010
ACM
13 years 11 months ago
Uncovering social spammers: social honeypots + machine learning
Web-based social systems enable new community-based opportunities for participants to engage, share, and interact. This community value and related services like search and advert...
Kyumin Lee, James Caverlee, Steve Webb
AIR
2005
119views more  AIR 2005»
13 years 7 months ago
An Assessment of Case-Based Reasoning for Spam Filtering
Because of the changing nature of spam, a spam filtering system that uses machine learning will need to be dynamic. This suggests that a case-based (memory-based) approach may work...
Sarah Jane Delany, Padraig Cunningham, Lorcan Coyl...
CORR
2000
Springer
126views Education» more  CORR 2000»
13 years 7 months ago
Learning to Filter Spam E-Mail: A Comparison of a Naive Bayesian and a Memory-Based Approach
We investigate the performance of two machine learning algorithms in the context of antispam filtering. The increasing volume of unsolicited bulk e-mail (spam) has generated a nee...
Ion Androutsopoulos, Georgios Paliouras, Vangelis ...