Lukas Kölsch

Sophie Hannah Bénéteau, Nicolas Goluboff, Lukas Kölsch et al.

APN functions play a central role as building blocks in the design of many block ciphers, serving as optimal functions to resist differential attacks. One of the most important properties of APN functions is their linearity, which is directly related to the Walsh spectrum of the function. In this paper, we establish two novel connections that allow us to derive strong conditions on the Walsh spectra of quadratic APN functions. We prove that the Walsh transform of a quadratic APN function $F$ operating on $n=2k$ bits is uniquely associated with a vector space partition of $\mathbb{F}_2^n$ and a specific blocking set in the corresponding projective space $PG(n-1,2)$. These connections allow us to prove a variety of results on the Walsh spectrum of $F$. We prove for instance that $F$ can have at most one component function of amplitude larger than $2^{3n/4}$. We also find the first nontrivial upper bound on the number of bent component functions of a quadratic APN function, and provide conditions for a function to be CCZ-equivalent to a permutation based on its number of bent components.

Faruk Göloğlu, Lukas Kölsch

We give a large family of almost perfect nonlinear (APN) permutations of finite vector spaces of every odd dimension divisible by three. We also give APN functions that are not bijective on even dimensions and related highly nonlinear functions. The functions we provide admit a so-called triprojective structure induced by the general linear group $\mathrm{GL}(3,2^m)$.

Lukas Kölsch, Björn Kriepke, Gohar M. Kyureghyan

We consider image sets of differentially $d$-uniform maps of finite fields. We present a lower bound on the image size of such maps and study their preimage distribution, by extending methods used for planar maps. We apply the results to study $d$-uniform Dembowski-Ostrom polynomials. Further, we focus on a particularly interesting case of APN maps on binary fields. We show that APN maps with the minimal image size must have a very special preimage distribution. We prove that for an even $n$ the image sets of several well-studied families of APN maps are minimal. We present results connecting the image sets of special maps with their Walsh spectrum. Especially, we show that the fact that several large classes of APN maps have the classical Walsh spectrum is explained by the minimality of their image sets. Finally, we present upper bounds on the image size of APN maps.