Correlated noise reduction for electromagnetic analysis

Hongying Liu, Xin Jin, Yukiyasu Tsunoo, Satoshi Goto

Research output: Contribution to journalArticle

3 Citations (Scopus)

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.

Original languageEnglish
Pages (from-to)185-195
Number of pages11
JournalIEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences
VolumeE96-A
Issue number1
DOIs
Publication statusPublished - 2013 Jan

Keywords

  • Correlated noise
  • Electromagnetic analysis (EMA)
  • Electromagnetic leakage
  • Power analysis
  • Singular value decomposition

ASJC Scopus subject areas

  • Electrical and Electronic Engineering
  • Computer Graphics and Computer-Aided Design
  • Applied Mathematics
  • Signal Processing

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