Filtering-based correlation power analysis (CPA) with signal envelopes against shuffling methods

Youngbae Jeon, Ji Won Yoon

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

The Correlation Power Analysis (CPA) is one of the powerful Side-Channel Analysis (SCA) methods to reveal the secret key using linear relationship between intermediate values and power consumption. To defense the analysis, many crypto-systems often embed the shuffling implementation which shuffles the order of operations to break the relationship between power consumption and processed information. Although the shuffling method increases the required number of power traces for deploying the CPA, it is still vulnerable if an attacker can classify or group the power traces by operations. In this work, we propose a new CPA technique by efficiently clustering the power traces using signal envelopes. We demonstrate theoretically reduced time complexity and tested our approach with the eight-shuffling AES implementations.

Original languageEnglish
Title of host publicationInformation Security Applications - 21st International Conference, WISA 2020, Revised Selected Papers
EditorsIlsun You
PublisherSpringer Science and Business Media Deutschland GmbH
Pages389-402
Number of pages14
ISBN (Print)9783030652982
DOIs
Publication statusPublished - 2020
Event21st International Conference on Information Security Applications, WISA 2020 - Jeju Island, Korea, Republic of
Duration: 2020 Aug 262020 Aug 28

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume12583 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference21st International Conference on Information Security Applications, WISA 2020
CountryKorea, Republic of
CityJeju Island
Period20/8/2620/8/28

Keywords

  • Clustering algorithm
  • Correlation Power Analysis (CPA)
  • Envelope
  • Shuffling method
  • Side-Channel Analysis

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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