5 research outputs found
Third-order nonlinearities of some biquadratic monomial Boolean functions
In this paper, we estimate the lower bounds on third-order
nonlinearities of some biquadratic monomial Boolean functions of the
form for all , where
\lambda \in \BBF_{2^n}^{*},
\begin{itemize}
\item [{(1)}],
are integers such that and .
\item [{(2)}] ,
is a positive integer such that and .
\end{itemize
Improved upper bound on root number of linearized polynomials and its application to nonlinearity estimation of Boolean functions
To determine the dimension of null space of any given linearized polynomial
is one of vital problems in finite field theory, with concern to design of
modern symmetric cryptosystems. But, the known general theory for this task is
much far from giving the exact dimension when applied to a specific linearized
polynomial. The first contribution of this paper is to give a better general
method to get more precise upper bound on the root number of any given
linearized polynomial. We anticipate this result would be applied as a useful
tool in many research branches of finite field and cryptography. Really we
apply this result to get tighter estimations of the lower bounds on the second
order nonlinearities of general cubic Boolean functions, which has been being
an active research problem during the past decade, with many examples showing
great improvements. Furthermore, this paper shows that by studying the
distribution of radicals of derivatives of a given Boolean functions one can
get a better lower bound of the second-order nonlinearity, through an example
of the monomial Boolean function over any
finite field \GF{n}
Probabilistic Higher Order Differential Attack and Higher Order Bent Functions
. We first show that a Feistel type block cipher is broken if the round function is approximated by a low degree vectorial Boolean function. The proposed attack is a generalization of the higher order differential attack to a probabilistic one. We next introduce a notion of higher order bent functions in order to prevent our attack. We then show their explicit constructions.
Towards Finding the Best Characteristics of Some Bit-oriented Block Ciphers and Automatic Enumeration of (Related-key) Differential and Linear Characteristics with Predefined Properties
In this paper, we investigate the Mixed-integer Linear Programming (MILP) modelling of the differential and linear behavior of a wide range of block ciphers. We point out that the differential behavior of an arbitrary S-box can be exactly described by a small system of linear inequalities.
~~~~~Based on this observation and MILP technique, we propose an automatic method for finding high probability (related-key) differential or linear characteristics of block ciphers. Compared with Sun {\it et al.}\u27s {\it heuristic} method presented in Asiacrypt 2014, the new method is {\it exact} for most ciphers in the sense that every feasible 0-1 solution of the MILP model generated by the new method corresponds to a valid characteristic, and therefore there is no need to repeatedly add valid cutting-off inequalities into the MILP model as is done in Sun {\it et al.}\u27s method; the new method is more powerful which allows us to get the {\it exact lower bounds} of the number of differentially or linearly active S-boxes; and the new method is more efficient which allows to obtain characteristic with higher probability or covering more rounds of a cipher (sometimes with less computational effort).
~~~~~Further, by encoding the probability information of the differentials of an S-boxes into its differential patterns, we present a novel MILP modelling technique which can be used to search for the characteristics with the maximal probability, rather than the characteristics with the smallest number of active S-boxes. With this technique, we are able to get tighter security bounds and find better characteristics.
~~~~~Moreover, by employing a type of specially constructed linear inequalities which can remove {\it exactly one} feasible 0-1 solution from the feasible region of an MILP problem, we propose a method for automatic enumeration of {\it all} (related-key) differential or linear characteristics with some predefined properties, {\it e.g.}, characteristics with given input or/and output difference/mask, or with a limited number of active S-boxes. Such a method is very useful in the
automatic (related-key) differential analysis, truncated (related-key) differential analysis, linear hull analysis, and the automatic construction of (related-key) boomerang/rectangle distinguishers.
~~~~~The methods presented in this paper are very simple and straightforward, based on which we implement a Python framework for automatic cryptanalysis, and extensive experiments are performed using this framework. To demonstrate the usefulness of these methods, we apply them to SIMON, PRESENT, Serpent, LBlock, DESL, and we obtain some improved cryptanalytic results