A more flexible countermeasure against side channel attacks using window method

Katsuyuki Okeya, Tsuyoshi Takagi

Research output: Chapter in Book/Report/Conference proceedingChapter

16 Citations (Scopus)

Abstract

Elliptic curve cryptosystem (ECC) is well-suited for the implementation on memory constraint environments due to its small key size. However, side channel attacks (SCA) can break the secret key of ECC on such devices, if the implementation method is not carefully considered. The scalar multiplication of ECC is particularly vulnerable to the SCA. In this paper we propose an SCA-resistant scalar multiplication method that is allowed to take any number of pre-computed points. The proposed scheme essentially intends to resist the simple power analysis (SPA), not the differential power analysis (DPA). Therefore it is different from the other schemes designed for resisting the DPA. The previous SPA-countermeasures based on window methods utilize the fixed pattern windows, so that they only take discrete table size. The optimal size is 2w-1 for w = 2,3,..., which was proposed by Okeya and Takagi. We play a different approach from them. The key idea is randomly (but with fixed probability) to generate two different patterns based on pre-computed points. The two distributions are indistinguishable from the view point of the SPA. The proposed probabilistic scheme provides us more flexibility for generating the pre-computed points - the designer of smart cards can freely choose the table size without restraint.

Original languageEnglish
Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
EditorsColin D. Walter, Cetin K. Koc, Christof Paar
PublisherSpringer Verlag
Pages397-410
Number of pages14
ISBN (Print)3540408339, 9783540408338
DOIs
Publication statusPublished - 2003

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume2779
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • Computer Science(all)

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