Adversarial Learning: A Critical Review and Active Learning Study
May 27, 2017 Β· Declared Dead Β· π International Workshop on Machine Learning for Signal Processing
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Authors
David J. Miller, Xinyi Hu, Zhicong Qiu, George Kesidis
arXiv ID
1705.09823
Category
cs.CR: Cryptography & Security
Citations
24
Venue
International Workshop on Machine Learning for Signal Processing
Last Checked
4 months ago
Abstract
This papers consists of two parts. The first is a critical review of prior art on adversarial learning, identifying some significant limitations of previous works. The second part is an experimental study considering adversarial active learning and an investigation of the efficacy of a mixed sample selection strategy for combating an adversary who attempts to disrupt the classifier learning.
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