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Title: Security Engineering for Machine Learning
Authors: Mcgraw, G.
Participants: Bonett, R.
Figueroa, H.
Shepardson, V.
Issue Date: 2019
Publisher: IEEE Explore
Series/Report no.: Computer, 2019, Vol 52, Issue 8, pp 54-57
Abstract: 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.
URI: http://tailieuso.tlu.edu.vn/handle/DHTL/10453
Appears in Collections:Tài liệu hỗ trợ nghiên cứu khoa học
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