Please use this identifier to cite or link to this item:
Title: Machine learning and hardware security : challenges and opportunities
Authors: Regazzoni, Francesco
Bhasin, Shivam
Pour, Amir Ali
Alshaer, Ihab
Aydin, Furkan
Aysu, Aydin
Beroulle, Vincent
Di Natale, Giorgio
Franzon, Paul
Hely, David
Homma, Naofumi
Ito, Akira
Jap, Dirmanto
Kashyap, Priyank
Polian, Ilia
Potluri, Seetal
Ueno, Rei
Vatajelu, Elena-Ioana
Yli-Mäyry, Ville
Keywords: Engineering::Computer science and engineering
Issue Date: 2020
Source: Regazzoni, F., Bhasin, S., Pour, A. A., Alshaer, I., Aydin, F., Aysu, A., Beroulle, V., Di Natale, G., Franzon, P., Hely, D., Homma, N., Ito, A., Jap, D., Kashyap, P., Polian, I., Potluri, S., Ueno, R., Vatajelu, E. & Yli-Mäyry, V. (2020). Machine learning and hardware security : challenges and opportunities. IEEE/ACM International Conference On Computer-Aided Design, Digest of Technical Papers, ICCAD, 2020-November, 1-6.
Journal: IEEE/ACM International Conference on Computer-Aided Design, Digest of Technical Papers, ICCAD
Abstract: Machine learning techniques have significantly changed our lives. They helped improving our everyday routines, but they also demonstrated to be an extremely helpful tool for more advanced and complex applications. However, the implications of hardware security problems under a massive diffusion of machine learning techniques are still to be completely understood. This paper first highlights novel applications of machine learning for hardware security, such as evaluation of post quantum cryptography hardware and extraction of physically unclonable functions from neural networks. Later, practical model extraction attack based on electromagnetic side-channel measurements are demonstrated followed by a discussion of strategies to protect proprietary models by watermarking them.
ISBN: 9781450380263
ISSN: 1558-2434
DOI: 10.1145/3400302.3416260
Research Centres: Temasek Laboratories @ NTU 
Rights: © 2020 Institute of Electrical and Electronics Engineers (IEEE). All rights reserved.
Fulltext Permission: none
Fulltext Availability: No Fulltext
Appears in Collections:TL Journal Articles

Citations 20

Updated on Jun 3, 2023

Web of ScienceTM
Citations 50

Updated on May 28, 2023

Page view(s)

Updated on Jun 4, 2023

Google ScholarTM




Items in DR-NTU are protected by copyright, with all rights reserved, unless otherwise indicated.