Side-Channel Analysis of Curve-25519 Based on Deep Learning
Authors: 
Zongnan Zhang, Meng Li, Xiaoxin An, Zhen Li, Zhe MaAuthors Info & Claims
Zongnan Zhang, Meng Li, Xiaoxin An, Zhen Li, Zhe MaAuthors Info & ClaimsPages 144 - 149
Abstract
This paper explores the integration of deep learning technology with Side-Channel Analysis (SCA) methods to effectively analyze the Curve-25519 algorithm implemented on an MCU chip. The Curve-25519 algorithm, protected by the security features of elliptical curve algorithms and constant-time operations, presents a challenge for low-cost, non-invasive SCA methods due to its robustness. This work focuses on the leakage of conditional judgment operations that occur before each point addition and point doubling operation. By identifying these information leakage points through SCA, electromagnetic radiation and power consumption information are collected and labeled. We conduct a dataset and transformed 1-dimensional signals into a 2D image for training. The trained model is subsequently used for testing. Experiments demonstrate that this method can effectively analyze leakage points in the Curve-25519 algorithm and help to improve the robustness of the algorithm.
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Published In
May 2024
439 pages
ISBN:9798400709562
DOI:10.1145/3665348
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Published: 03 July 2024
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GAIIS 2024
GAIIS 2024: 2024 International Conference on Generative Artificial Intelligence and Information Security
May 10 - 12, 2024
Kuala Lumpur, Malaysia
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