@proceedings {citation179,
	title = {Exploiting machine learning to subvert your spam filter},
	journal = {1st Usenix Workshop on Large-Scale Exploits and Emergent Threats},
	year = {2008},
	month = {04/2008},
	publisher = {USENIX Association},
	address = {San Francisco, CA},
	abstract = {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{\textquoteright}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.},
	url = {http://www.usenix.org/events/leet08/tech/full_papers/nelson/nelson.pdf},
	author = {Blaine Nelson and Marco Barreno and Fuching Jack Chi and Anthony D. Joseph and Benjamin I. P. Rubinstein and Udam Saini and Charles Sutton and J. D. Tygar and Kai Xia}
}
