On the Feasibility of using Machine Learning for an Enhanced Physical Security of Embedded Devices-Reference-Cited by-同舟云学术

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On the Feasibility of using Machine Learning for an Enhanced Physical Security of Embedded Devices

Published:2022-05 Issue: Volume: Page:
ISSN:
Container-title:2022 2nd International Conference of Smart Systems and Emerging Technologies (SMARTTECH)
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Author:

Halak Basel¹,Vincent Hugo²,Hall Christian¹,Fathir Syed Abdul¹,Kit Nelson Chow Wai¹,Raymonde Ruwaydah Widaad¹

Affiliation:

1. University of Southampton,UK

2. ARM Ltd

Funder

royal academy of engineering

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9842388/9842335/09842400.pdf?arnumber=9842400

Reference12 articles.

1. Post-deployment trust evaluation in wireless cryptographic ICs;jin;2012 Design Automation & Test in Europe Conference & Exhibition (DATE),2012

2. System-level tamper protection using MSP mcus;peeters;Texas Instruments,2016

3. Ageing of Integrated Circuits

4. NIST;Security Requirements for Cryptographic Modules FIPS PUB 140–2,2019

Cited by 1 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Toward Autonomous Physical Security Defenses Using Machine Learning;IEEE Access;2022

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