Correlated Noise Reduction for Electromagnetic Analysis

Hongying LIU; Xin JIN; Yukiyasu TSUNOO; Satoshi GOTO

doi:10.1587/transfun.E96.A.185

Correlated Noise Reduction for Electromagnetic Analysis

Hongying LIU, Xin JIN, Yukiyasu TSUNOO, Satoshi GOTO

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Electromagnetic emissions leak confidential data of cryptographic devices. Electromagnetic Analysis (EMA) exploits such emission for cryptanalysis. The performance of EMA dramatically decreases when correlated noise, which is caused by the interference of clock network and exhibits strong correlation with encryption signal, is present in the acquired EM signal. In this paper, three techniques are proposed to reduce the correlated noise. Based on the observation that the clock signal has a high variance at the signal edges, the first technique: single-sample Singular Value Decomposition (SVD), extracts the clock signal with only one EM sample. The second technique: multi-sample SVD is capable of suppressing the clock signal with short sampling length. The third one: averaged subtraction is suitable for estimation of correlated noise when background samplings are included. Experiments on the EM signal during AES encryption on the FPGA and ASIC implementation demonstrate that the proposed techniques increase SNR as much as 22.94 dB, and the success rates of EMA show that the data-independent information is retained and the performance of EMA is improved.

Publication: IEICE TRANSACTIONS on Fundamentals Vol.E96-A No.1 pp.185-195

Publication Date: 2013/01/01

Publicized

Online ISSN: 1745-1337

DOI: 10.1587/transfun.E96.A.185

Type of Manuscript: Special Section PAPER (Special Section on Cryptography and Information Security)

Category: Implementation

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Hongying LIU, Xin JIN, Yukiyasu TSUNOO, Satoshi GOTO, "Correlated Noise Reduction for Electromagnetic Analysis" in IEICE TRANSACTIONS on Fundamentals, vol. E96-A, no. 1, pp. 185-195, January 2013, doi: 10.1587/transfun.E96.A.185.
Abstract: Electromagnetic emissions leak confidential data of cryptographic devices. Electromagnetic Analysis (EMA) exploits such emission for cryptanalysis. The performance of EMA dramatically decreases when correlated noise, which is caused by the interference of clock network and exhibits strong correlation with encryption signal, is present in the acquired EM signal. In this paper, three techniques are proposed to reduce the correlated noise. Based on the observation that the clock signal has a high variance at the signal edges, the first technique: single-sample Singular Value Decomposition (SVD), extracts the clock signal with only one EM sample. The second technique: multi-sample SVD is capable of suppressing the clock signal with short sampling length. The third one: averaged subtraction is suitable for estimation of correlated noise when background samplings are included. Experiments on the EM signal during AES encryption on the FPGA and ASIC implementation demonstrate that the proposed techniques increase SNR as much as 22.94 dB, and the success rates of EMA show that the data-independent information is retained and the performance of EMA is improved.
URL: https://global.ieice.org/en_transactions/fundamentals/10.1587/transfun.E96.A.185/_p

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@ARTICLE{e96-a_1_185,
author={Hongying LIU, Xin JIN, Yukiyasu TSUNOO, Satoshi GOTO, },
journal={IEICE TRANSACTIONS on Fundamentals},
title={Correlated Noise Reduction for Electromagnetic Analysis},
year={2013},
volume={E96-A},
number={1},
pages={185-195},
abstract={Electromagnetic emissions leak confidential data of cryptographic devices. Electromagnetic Analysis (EMA) exploits such emission for cryptanalysis. The performance of EMA dramatically decreases when correlated noise, which is caused by the interference of clock network and exhibits strong correlation with encryption signal, is present in the acquired EM signal. In this paper, three techniques are proposed to reduce the correlated noise. Based on the observation that the clock signal has a high variance at the signal edges, the first technique: single-sample Singular Value Decomposition (SVD), extracts the clock signal with only one EM sample. The second technique: multi-sample SVD is capable of suppressing the clock signal with short sampling length. The third one: averaged subtraction is suitable for estimation of correlated noise when background samplings are included. Experiments on the EM signal during AES encryption on the FPGA and ASIC implementation demonstrate that the proposed techniques increase SNR as much as 22.94 dB, and the success rates of EMA show that the data-independent information is retained and the performance of EMA is improved.},
keywords={},
doi={10.1587/transfun.E96.A.185},
ISSN={1745-1337},
month={January},}

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TY - JOUR
TI - Correlated Noise Reduction for Electromagnetic Analysis
T2 - IEICE TRANSACTIONS on Fundamentals
SP - 185
EP - 195
AU - Hongying LIU
AU - Xin JIN
AU - Yukiyasu TSUNOO
AU - Satoshi GOTO
PY - 2013
DO - 10.1587/transfun.E96.A.185
JO - IEICE TRANSACTIONS on Fundamentals
SN - 1745-1337
VL - E96-A
IS - 1
JA - IEICE TRANSACTIONS on Fundamentals
Y1 - January 2013
AB - Electromagnetic emissions leak confidential data of cryptographic devices. Electromagnetic Analysis (EMA) exploits such emission for cryptanalysis. The performance of EMA dramatically decreases when correlated noise, which is caused by the interference of clock network and exhibits strong correlation with encryption signal, is present in the acquired EM signal. In this paper, three techniques are proposed to reduce the correlated noise. Based on the observation that the clock signal has a high variance at the signal edges, the first technique: single-sample Singular Value Decomposition (SVD), extracts the clock signal with only one EM sample. The second technique: multi-sample SVD is capable of suppressing the clock signal with short sampling length. The third one: averaged subtraction is suitable for estimation of correlated noise when background samplings are included. Experiments on the EM signal during AES encryption on the FPGA and ASIC implementation demonstrate that the proposed techniques increase SNR as much as 22.94 dB, and the success rates of EMA show that the data-independent information is retained and the performance of EMA is improved.
ER -