Paper 2017/204 Original: eprint.iacr.org/2017/204 ↗
Linear Cryptanalysis Using Low-bias Linear Approximations
Abstract
This paper deals with linear approximations having absolute bias smaller than $2^{-\frac{n}{2}}$ which were previously believed to be unusable for a linear attack. We show how a series of observations which are individually not statistically significant can be used to create a $\chi^2$ distinguisher. This is different from previous works which combined a series of significant observations to reduce the data complexity of a linear attack. We test the distinguisher on a real-world cipher and show that it can be used to improve previous results.
Metadata
- Available format(s)
PDF- Category
- Secret-key cryptography
- Publication info
- Preprint.
- History
- 2017-03-01: last updated
- 2017-03-01: published
- Short URL
- https://ia.cr/2017/204
- License
- https://creativecommons.org/licenses/by/4.0/
BibTeX
@misc{cryptoeprint:2017/204,
author = {Tomer Ashur and Daniël Bodden and Orr Dunkelman},
title = {Linear Cryptanalysis Using Low-bias Linear Approximations},
howpublished = {Cryptology {ePrint} Archive, Paper 2017/204},
year = {2017},
url = {https://eprint.iacr.org/2017/204}
}