小波信号去噪在电磁走线中的应用

Mariana Safta, P. Svasta, Mihai Dima
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引用次数: 1

摘要

侧信道攻击(SCA)越来越受到世界各地黑客的欢迎,因为它们可以通过探索物理数据泄漏来访问存储在电路中的敏感信息。最著名的SCA是基于功耗(例如差分/简单功率分析)、电磁辐射(例如差分/简单电磁分析)、执行加密操作时消耗的时间分析和故障诱导(例如光学故障)。功率和电磁分析都需要通过使用专门的设备获取大量的走线。当环境条件恶劣,捕获的迹线有噪声,难以从噪声中提取信号时,就会出现这个问题。在本文中,我们专注于寻找一种最佳机制来降噪从微控制器发出的电磁辐射中捕获的信号。为了做到这一点,使用小波函数,并根据所应用的阈值水平和方法对结果进行比较。小波函数是一种综合工具,具有信号去噪和数据压缩等应用。本文介绍了所得到的所有结果,并对这一过程进行了总结。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Wavelet signal denoising applied on electromagnetic traces
Side-channel attacks (SCA) have become more and more popular among hackers all over the world because they can provide access to sensitive information stored in a circuit, only by exploring physical data leakages. The most well-known SCA's are based on power consumption (e.g. Differential/Simple Power Analysis), electromagnetic radiations (e.g. Differential/Simple Electromagnetic Analysis), analyze of consumed time while performing cryptographic operations and inducing of faults (e.g. Optical Faults). Both power and electromagnetic analysis require acquiring a large number of traces by using specialized equipment. The problem appears when the environmental conditions are rough and the captured traces are noisy, making it hard to extract the signal from the noise. In this paper we focus on finding an optimal mechanism to denoise the signals captured from the electromagnetic radiations emitted by a microcontroller. In order to do so, Wavelet functions were used and results were compared depending on the threshold's levels and methods that were applied. Wavelet functions are a comprehensive tool with applications like signal denoising and data compression. All the obtained results are presented in this paper and conclusions regarding this process are drawn.
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