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Open Access
Efficient Algorithms for Sign Detection in RNS Using Approximate Reciprocals

Shinichi KAWAMURA, Yuichi KOMANO, Hideo SHIMIZU, Saki OSUKA, Daisuke FUJIMOTO, Yuichi HAYASHI, Kentaro IMAFUKU

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Summary :

The residue number system (RNS) is a method for representing an integer x as an n-tuple of its residues with respect to a given set of moduli. In RNS, addition, subtraction, and multiplication can be carried out by independent operations with respect to each modulus. Therefore, an n-fold speedup can be achieved by parallel processing. The main disadvantage of RNS is that we cannot efficiently compare the magnitude of two integers or determine the sign of an integer. Two general methods of comparison are to transform a number in RNS to a mixed-radix system or to a radix representation using the Chinese remainder theorem (CRT). We used the CRT to derive an equation approximating a value of x relative to M, the product of moduli. Then, we propose two algorithms that efficiently evaluate the equation and output a sign bit. The expected number of steps of these algorithms is of order n. The algorithms use a lookup table that is (n+3) times as large as M, which is reasonably small for most applications including cryptography.

Publication
IEICE TRANSACTIONS on Fundamentals Vol.E104-A No.1 pp.121-134
Publication Date
2021/01/01
Publicized
Online ISSN
1745-1337
DOI
10.1587/transfun.2020CIP0020
Type of Manuscript
Special Section PAPER (Special Section on Cryptography and Information Security)
Category

Authors

Shinichi KAWAMURA
  ECSEC Technical Research Association,Toshiba Corporation,National Institute of Advanced Industrial Science and Technology
Yuichi KOMANO
  Toshiba Corporation
Hideo SHIMIZU
  Toshiba Corporation
Saki OSUKA
  Nara Institute of Science and Technology
Daisuke FUJIMOTO
  Nara Institute of Science and Technology
Yuichi HAYASHI
  National Institute of Advanced Industrial Science and Technology,Nara Institute of Science and Technology
Kentaro IMAFUKU
  National Institute of Advanced Industrial Science and Technology

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