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2008

Exploiting Machine Learning to Subvert Your Spam Filter

9 years 3 months ago
Exploiting Machine Learning to Subvert Your Spam Filter
Using statistical machine learning for making security decisions introduces new vulnerabilities in large scale systems. This paper shows how an adversary can exploit statistical machine learning, as used in the SpamBayes spam filter, to render it useless--even if the adversary's access is limited to only 1% of the training messages. We further demonstrate a new class of focused attacks that successfully prevent victims from receiving specific email messages. Finally, we introduce two new types of defenses against these attacks.
Blaine Nelson, Marco Barreno, Fuching Jack Chi, An
Added 02 Oct 2010
Updated 02 Oct 2010
Type Conference
Year 2008
Where NSDI
Authors Blaine Nelson, Marco Barreno, Fuching Jack Chi, Anthony D. Joseph, Benjamin I. P. Rubinstein, Udam Saini, Charles Sutton, J. Doug Tygar, Kai Xia
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