@proceedings {citation178,
	title = {Evading Anomaly Detection through Variance Injection Attacks on PCA },
	journal = {11th International Symposium on Recent Advances in Intrusion Detection (RAID{\textquoteright}08)},
	year = {2008},
	month = {09/2008},
	pages = {394-395},
	publisher = {Springer-Verlag},
	address = {Boston, MA},
	abstract = {Whenever machine learning is applied to security problems, it is important to measure vulnerabilities to adversaries who poison the training data. We demonstrate the impact of variance injection schemes on PCA-based network-wide volume anomaly detectors, when a single compromised PoP injects chaff into the network. These schemes can increase the chance of evading detection by sixfold, for DoS attacks.},
	issn = {978-3-540-87402-7},
	author = {Benjamin I. P. Rubinstein and Blaine Nelson and Ling Huang and Anthony D. Joseph and Shing-hon Lau and Nina Taft and J. D. Tygar}
}
