Issue No. 05 - September/October (2011 vol. 15)
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/MIC.2011.112
J.D. Tygar , University of California, Berkeley
<p>The author briefly introduces the emerging field of adversarial machine learning, in which opponents can cause traditional machine learning algorithms to behave poorly in security applications. He gives a high-level overview and mentions several types of attacks, as well as several types of defenses, and theoretical limits derived from a study of near-optimal evasion.</p>
machine learning, adversarial machine learning, computer security, spam email, intrusion detection
J. Tygar, "Adversarial Machine Learning," in IEEE Internet Computing, vol. 15, no. , pp. 4-6, 2011.