You are looking at a specific version 20050415:075947 of this paper. See the latest version.

Paper 2004/214

Classification of Highly Nonlinear Boolean Power Functions with a Randomised Algorithm for Checking Normality

An Braeken, Christopher Wolf, and Bart Preneel

Abstract

A Boolean function is called normal if it is constant on flats of certain dimensions. This property is relevant for the construction and analysis of cryptosystems. This paper presents an asymmetric Monte Carlo algorithm to determine whether a given Boolean function is normal. Our algorithm is far faster than the best known (deterministic) algorithm of Daum et al. In a first phase, it checks for flats of low dimension whether the given Boolean function is constant on them and combines such flats to flats of higher dimension in a second phase. This way, the algorithm is much faster than exhaustive search. Moreover, the algorithm benefits from randomising the first phase. In addition, by evaluating several flats implicitly in parallel, the time-complexity of the algorithm decreases further. As an application, we determine the level of normality for several, highly nonlinear Boolean power functions.

Metadata
Available format(s)
PDF PS
Category
Secret-key cryptography
Publication info
Published elsewhere. Unknown where it was published
Keywords
boolean functionsnormalitypower-functionsMonte Carlo
Contact author(s)
Christopher Wolf @ Esat KULeuven ac be
History
2005-04-15: last of 5 revisions
2004-08-30: received
See all versions
Short URL
https://ia.cr/2004/214
License
Creative Commons Attribution
CC BY
Note: In order to protect the privacy of readers, eprint.iacr.org does not use cookies or embedded third party content.