Adversarial Learning: A Critical Review and Active Learning Study

May 27, 2017 Β· Declared Dead Β· πŸ› 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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