Deep Learning Gradient Visualization-Based Pre-Silicon Side-Channel Leakage Location-Reference-Cited by-同舟云学术

Deep Learning Gradient Visualization-Based Pre-Silicon Side-Channel Leakage Location

Published:2024 Issue: Volume:19 Page:2340-2355
ISSN:1556-6013
Container-title:IEEE Transactions on Information Forensics and Security
language:
Short-container-title:IEEE Trans.Inform.Forensic Secur.

Author:

Li Yanbin¹^ORCID,Zhu Jiajie²,Liu Zhe³^ORCID,Tang Ming⁴^ORCID,Ren Shougang⁵

Affiliation:

1. School of Software, Shandong University, Jinan, China

2. State Key Laboratory of Cryptology, Beijing, China

3. Zhejiang Laboratory, Hangzhou, China

4. School of Cyber Science and Engineering and the Key Laboratory of Aerospace Information Security and Trusted Computing, Ministry of Education, Wuhan University, Wuhan, China

5. College of Artificial Intelligence, Nanjing Agricultural University, Nanjing, China

Funder

National Natural Science Foundation of China

Henan Key Laboratory of Network Cryptography Technology

Natural Science Foundation of Jiangsu Province

High Level Personnel Project of Jiangsu Province

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx7/10206/10319981/10381750.pdf?arnumber=10381750

Reference51 articles.

1. Electromagnetic Side Channel Information Leakage Created by Execution of Series of Instructions in a Computer Processor

2. Intrinsic Resiliency of S-Boxes Against Side-Channel Attacks–Best and Worst Scenarios

3. Diffusional Side-Channel Leakage From Unrolled Lightweight Block Ciphers: A Case Study of Power Analysis on PRINCE

4. Efficient Profiled Side-Channel Analysis of Masked Implementations, Extended

5. An Efficient Side-Channel Protected AES Implementation with Arbitrary Protection Order

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