Research on Cross-Device Bypass Attacks Based on Deep Learning-Reference-Cited by-同舟云学术

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Research on Cross-Device Bypass Attacks Based on Deep Learning

Published:2023-10-20 Issue: Volume: Page:
ISSN:
Container-title:2023 IEEE 7th International Symposium on Electromagnetic Compatibility (ISEMC)
language:
Short-container-title:

Author:

Zhang Hongxin¹,Zhang Qingqing²,Wang Danzhi²,Fan Fan³,Shu Lei³

Affiliation:

1. School of Electronic Engineering, Beijing University of Posts and Telecommunications,Beijing Key Laboratory of Work Safety Intelligent Monitoring,Beijing,China,100876

2. School of Electronic Engineering, Beijing University of Posts and Telecommunications,Beijing,China,100876

3. Beijing Microelectronics Technology Institute,Beijing,China,100076

Funder

National Natural Science Foundation of China

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10370006/10368602/10370077.pdf?arnumber=10370077

Reference9 articles.

1. Study of deep learning techniques for side-channel analysis and introduction to ascad database[J];Emmanuel;CoRR,2018

2. AES wireless keyboard: Template attack for eavesdropping[J];Kim

3. A Formal Study of Power Variability Issues and Side-Channel Attacks for Nanoscale Devices

4. The SIMON and SPECK families of lightweight block ciphers[J];Beaulieu,2013

5. Correlation Power Analysis of Lightweight Block Ciphers: From Theory to Practice

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