TripletPower: Deep-Learning Side-Channel Attacks over Few Traces-Reference-Cited by-同舟云学术

TripletPower: Deep-Learning Side-Channel Attacks over Few Traces

Published:2023-05-01 Issue: Volume: Page:
ISSN:
Container-title:2023 IEEE International Symposium on Hardware Oriented Security and Trust (HOST)
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Author:

Wang Chenggang¹,Dani Jimmy¹,Reilly Shane¹,Brownfield Austen¹,Wang Boyang¹,Emmert John M.¹

Affiliation:

1. University of Cincinnati

Funder

National Science Foundation

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10132842/10132914/10133495.pdf?arnumber=10133495

Reference51 articles.

1. SCAUL: Power Side-Channel Analysis With Unsupervised Learning

2. Ranking Loss: Maximizing the Success Rate in Deep Learning Side-Channel Analysis;zaid;IACR Transactions on Cryptographic Hardware and Embedded Systems,2021

3. The curse of Class Imbalance and Conflicting Metrics with Machine Learning for Side-Channel Evaluations;picek;IACR Transactions on Cryptographic Hardware and Embedded Systems,2019

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