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Robust Machine Learning Systems: Challenges,Current Trends, Perspectives, and the Road Ahead
- Authors
- Shafique, Muhammad; Naseer, Mahum; Theocharides, Theocharis; Kyrkou, Christos; Mutlu, Onur; Orosa, Lois; Choi, Jungwook
- Issue Date
- Apr-2020
- Publisher
- IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
- Keywords
- Training data; Artificial neural networks; Reliability; Smart devices; Hardware; Machine learning
- Citation
- IEEE DESIGN & TEST, v.37, no.2, pp.30 - 57
- Indexed
- SCIE
SCOPUS
- Journal Title
- IEEE DESIGN & TEST
- Volume
- 37
- Number
- 2
- Start Page
- 30
- End Page
- 57
- ISSN
- 2168-2356
- Abstract
- Currently, machine learning (ML) techniques are at the heart of smart cyber-physical systems (CPS) and Internet-of-Things (IoT). This article discusses various challenges and probable solutions for security attacks on these ML-inspired hardware and software techniques. -Partha Pratim Pande, Washington State University
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Related Researcher
- Choi, Jung wook
- COLLEGE OF ENGINEERING (SCHOOL OF ELECTRONIC ENGINEERING)