The Community for Technology Leaders
RSS Icon
Issue No.05 - September/October (2011 vol.15)
pp: 4-6
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.D. Tygar, "Adversarial Machine Learning", IEEE Internet Computing, vol.15, no. 5, pp. 4-6, September/October 2011, doi:10.1109/MIC.2011.112
45 ms
(Ver 2.0)

Marketing Automation Platform Marketing Automation Tool