Security Engineering for Machine Learning

Artificial intelligence is in the midst of a popular resurgence in the guise of machine learning (ML). Neural networks and deep learning architectures have been shown empirically to solve many real-world problems. We ask what kinds of risks ML systems pose in terms of security engineering and softwa...

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Bibliographic Details
Published in:Computer (Long Beach, Calif.) Calif.), 2019-08, Vol.52 (8), p.54-57
Main Authors: Mcgraw, Gary, Bonett, Richie, Figueroa, Harold, Shepardson, Victor
Format: Article
Language:English
Subjects:
Artificial intelligence
Data mining
Data models
Engineering education
Machine learning
Neural networks
Security
Software engineering
Taxonomy
Training
Training data
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Summary:Artificial intelligence is in the midst of a popular resurgence in the guise of machine learning (ML). Neural networks and deep learning architectures have been shown empirically to solve many real-world problems. We ask what kinds of risks ML systems pose in terms of security engineering and software security.
ISSN:0018-9162
1558-0814
DOI:10.1109/MC.2019.2909955