Mixed-Integer Linear Programming (MILP) modeling has become an important tool for both the analysis and the design of symmetric cryptographic primitives. The bit-wise modeling of their nonlinear components, especially the S-boxes, is of particular interest since it allows more informative analysis compared to word-oriented models focusing on counting active S-boxes. At the same time, the size of these models, especially in terms of the number of required inequalities, tends to significantly influence and ultimately limit the applicability of this method to real-world ciphers, especially for larger number of rounds.

It is therefore of great cryptographic significance to study optimal linear inequality descriptions for Boolean functions. The pioneering works of Abdelkhalek et al. (FSE 2017), Boura and Coggia (FSE 2020) and Li and Sun (FSE 2023) provided various heuristic techniques for this computationally hard problem, decomposing it into two algorithmic steps, coined Problem 1 and Problem 2, with the latter being identical to the well-known NP-hard set cover problem, for which there are many heuristic and exact algorithms in the literature.

In this paper, we introduce a novel and efficient branch-and-bound algorithm for generating all minimal, non-redundant candidate inequalities that satisfy a given Boolean function, therefore solving Problem 1 in an optimal manner without relying on heuristics. We furthermore prove that our algorithm correctly computes optimal solutions. Using a number of dedicated optimizations, it provides significantly improved runtimes compared to previous approaches and allows the optimal modeling of the difference distribution tables (DDT) and linear approximation tables (LAT) of many practically used S-boxes. The source code for our algorithm is publicly available as a tool for researchers and practitioners in symmetric cryptography.

In order to maintain a similar security level in a post-quantum setting, many symmetric primitives should have to double their keys and increase their state sizes. So far, no generic way for doing this is known that would provide convincing quantum security guarantees. In this paper we propose a new generic construction, QuEME, that allows one to double the key and the state size of a block cipher in such a way that a decent level of quantum security is guaranteed. The QuEME design is inspired by the ECB-Mix-ECB (EME) construction, but is defined for a different choice of mixing function than what we have seen before, in order to withstand a new quantum superposition attack that we introduce as a side result: this quantum superposition attack exhibits a periodic property found in collisions and breaks EME and a large class of its variants. We prove that QuEME achieves n-bit security in the classical setting, where n is the block size of the underlying block cipher, and at least (n/6)-bit security in the quantum setting. We finally propose a concrete instantiation of this construction, called Double-AES, that is built with variants of the standardized AES-128 block cipher.

In this paper we study search problems that arise very often in cryptanalysis: nested search problems, where each search layer has known degrees of freedom and/or constraints. A generic quantum solution for such problems consists of nesting Grover's quantum search algorithm or amplitude amplification (QAA) by Brassard et al., obtaining up to a square-root speedup on classical algorithms. However, the analysis of nested Grover or QAA is complex and introduces technicalities that in previous works are handled in a case-by-case manner. Moreover, straightforward nesting of l layers multiplies the complexity by a constant factor (pi/2)^l.

In this paper, we aim to remedy both these issues and introduce a generic framework and tools to transform a classical nested search into a quantum procedure. It improves the state-of-the-art in three ways: 1) our framework results in quantum procedures that are significantly simpler to describe and analyze; 2) it reduces the overhead factor from (pi/2)^l to sqrt(l); 3) it is simpler to apply and optimize, without needing manual quantum analysis. We give generic complexity formulas and show that for concrete instances, numerical optimizations enable further improvements, reducing even more the gap to an exact quadratic speedup.

We demonstrate our framework by giving a tighter analysis of quantum attacks on reduced-round AES.

In ASIACRYPT 2019, Andreeva et al. introduced a new symmetric key primitive called the forkcipher, designed for lightweight applications handling short messages. A forkcipher is a keyed function with a public tweak, featuring fixed-length input and fixed-length (expanding) output. They also proposed a specific forkcipher, ForkSkinny, based on the tweakable block cipher SKINNY, and its security was evaluated through cryptanalysis. Since then, several efficient AEAD and MAC schemes based on forkciphers have been proposed, catering not only to short messages but also to various purposes such as leakage resilience and cloud security. While forkciphers have proven to be efficient solutions for designing AEAD schemes, the area of forkcipher design remains unexplored, particularly the lack of provably secure forkcipher constructions.

In this work, we propose forkcipher design for various tweak lengths, based on a block cipher as the underlying primitive. We provide proofs of security for these constructions, assuming the underlying block cipher behaves as an ideal block cipher. First, we present a forkcipher, $\widetilde{\textsf{F}}1$, for an $n$-bit tweak and prove its optimal ($n$-bit) security. Next, we propose another construction, $\widetilde{\textsf{F}}2$, for a $2n$-bit tweak, also proving its optimal ($n$-bit) security. Finally, we introduce a construction, $\widetilde{\textsf{F}}r$, for a general $rn$-bit tweak, achieving $n$-bit security.