Dataset Security for Machine Learning: Data Poisoning, Backdoor Attacks, and Defenses

As machine learning systems grow in scale, so do their training data requirements, forcing practitioners to automate and outsource the curation of training data in order to achieve state-of-the-art performance. The absence of trustworthy human supervision over the data collection process exposes org...

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Veröffentlicht in:	IEEE transactions on pattern analysis and machine intelligence Jg. 45; H. 2; S. 1563 - 1580
Hauptverfasser:	Goldblum, Micah, Tsipras, Dimitris, Xie, Chulin, Chen, Xinyun, Schwarzschild, Avi, Song, Dawn, Madry, Aleksander, Li, Bo, Goldstein, Tom
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	United States IEEE 01.02.2023 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:	backdoor attacks Data collection Data models Data poisoning dataset security Datasets Machine learning Security Servers Toxicology Training Training data Unsolicited e-mail
ISSN:	0162-8828, 1939-3539, 2160-9292, 1939-3539
Online-Zugang:	Volltext
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