Performance enhancement of differential power analysis attacks with signal companding methods

Jeong Choon Ryoo, Dong Guk Han, Sung Kyoung Kim, Sangjin Lee

Research output: Contribution to journalArticlepeer-review

10 Citations (Scopus)


Among previous proposed side channel analysis (SCA) methods, differential power analysis (DPA) based on the statistical characteristics of collected signals has been known as an efficient attack for uncovering the secret key of cryptosystems. However, the attack performance of this method is affected very much by the temporal misalignment and noise of collected side channel signals. In this letter, we propose a new method to surmount the noise problem in DPA. The performance of the proposed method is then evaluated while analyzing the power consumption signals of microcontroller chip during a DES operation. When we compare the experimental results with respect to the needed number of traces to uncover the secret key, our proposed method shows a performance enhancement of 33% in the time domain and 50% in the frequency domain without a time burden.

Original languageEnglish
Pages (from-to)625-628
Number of pages4
JournalIEEE Signal Processing Letters
Publication statusPublished - 2008

Bibliographical note

Funding Information:
Manuscript received December 31, 2007; revised June 04, 2008. This work was supported in part by the MKE (Ministry of Knowledge Economy), Korea, under the ITRC (Information Technology Research Center) support program supervised by the IITA (Institute of Information Technology Advancement)" (IITA-2008-(C1090-0801-0025)) and in part by the IT R&D program of MKE/IITA. [2005-S-088-04, Development of security technology for secure RFID/USN service]. The associate editor coordinating the review of this manuscript and approving it for publication was Dr. Per Lowenborg.


  • A-law
  • Companding
  • Correlation power analysis
  • Differential power analysis
  • Side channel analysis

ASJC Scopus subject areas

  • Signal Processing
  • Electrical and Electronic Engineering
  • Applied Mathematics


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