Attacking High-Performance SBCs: A Generic Preprocessing Framework for EMA

For the high-performance single-board computers (SBCs) running an operating system, side-channel attacks usually come at high analytical costs, requiring millions of traces. This work uses the case of electromagnetic attacks on encryption services in real-world SBCs to explore how various preprocessing methods can reduce the attack costs for such devices. Specifically, we propose a general preprocessing framework that effectively combines multiple preprocessing methods based on their inherent characteristics. Utilizing this framework, we design a four-layer preprocessing scheme that significantly reduces the number of traces for key recovery. The experimental results show that, when the attack success rate reaches 80 percent, the proposed preprocessing scheme reduces the number of traces required by a factor of approximately 10 compared to the latest alignment algorithm on the Raspberry Pi 2B. Our research demonstrates the feasibility of conducting low-cost side-channel attacks on SBCs, further emphasizing the need to protect sensitive applications running on these devices.

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Publication Details

Published
2024-12-17
DOI
https://doi.org/10.1109/trustcom63139.2024.00056
Primary Topic
Network Security and Intrusion Detection
Type
article
Field-Weighted Citation Impact
0.00

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article

Attacking High-Performance SBCs: A Generic Preprocessing Framework for EMA

Jingdian Ming, Yiwen Gao, Debao Wang, Yongbin Zhou et al.
Network Security and Intrusion Detection
article

Attacking High-Performance SBCs: A Generic Preprocessing Framework for EMA

Jingdian Ming, Yiwen Gao, Debao Wang, Yongbin Zhou, Xian Feng Huang
article en

Abstract

For the high-performance single-board computers (SBCs) running an operating system, side-channel attacks usually come at high analytical costs, requiring millions of traces. This work uses the case of electromagnetic attacks on encryption services in real-world SBCs to explore how various preprocessing methods can reduce the attack costs for such devices. Specifically, we propose a general preprocessing framework that effectively combines multiple preprocessing methods based on their inherent characteristics. Utilizing this framework, we design a four-layer preprocessing scheme that significantly reduces the number of traces for key recovery. The experimental results show that, when the attack success rate reaches 80 percent, the proposed preprocessing scheme reduces the number of traces required by a factor of approximately 10 compared to the latest alignment algorithm on the Raspberry Pi 2B. Our research demonstrates the feasibility of conducting low-cost side-channel attacks on SBCs, further emphasizing the need to protect sensitive applications running on these devices.

Nanjing University of Science and Technology (CN)
National Natural Science Foundation of China
Openalex Percentile: Top 65%
Network Security and Intrusion Detection
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