DocumentCode :
1317663
Title :
Adversarial Machine Learning
Author :
Tygar, J.D.
Author_Institution :
University of California, Berkeley
Volume :
15
Issue :
5
fYear :
2011
Firstpage :
4
Lastpage :
6
Abstract :
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.
Keywords :
adversarial machine learning; computer security; intrusion detection; machine learning; spam email;
fLanguage :
English
Journal_Title :
Internet Computing, IEEE
Publisher :
ieee
ISSN :
1089-7801
Type :
jour
DOI :
10.1109/MIC.2011.112
Filename :
6015575
Link To Document :
بازگشت