Welcome to the resource topic for 2002/099
A New Statistical Testing for Symmetric Ciphers and Hash Functions
Authors: Eric FiliolAbstract:
This paper presents a new, powerful statistical testing of symmetric
ciphers and hash functions which allowed us to detect biases in both
of these systems where previously known tests failed. We first give a
complete characterization of the Algebraic Normal Form (ANF) of
random Boolean functions by means of the Möbius transform. Then we
built a new testing based on the comparison between the structure of
the different Boolean functions Algebraic Normal Forms characterizing
symmetric ciphers and hash functions and those of purely random
Boolean functions. Detailed testing results on several cryptosystems
are presented. As a main result we show that AES, DES Snow and
Lili-128 fail all or part of the tests and thus present strong biases.
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