International Association
for Cryptologic Research

Advanced cryptographic protocols such as Zero-knowledge (ZK) proofs of knowledge, widely used in cryptocurrency applications such as Zcash, Monero, Filecoin, Tezos, Topos, demand new cryptographic hash functions that are efficient not only over the binary field $\F_2$, but also over large fields of prime characteristic $\F_p$. This need has been acknowledged by the wider community and new so-called Arithmetization-Oriented (AO) hash functions have been proposed, e.g. MiMC-Hash, Rescue, Poseidon, ReinforcedConcrete and Griffin to name a few. In this paper we propose Anemoi: a new family of ZK-friendly permutations, that can be used to construct efficient hash functions and compression functions. The main features of these algorithms are that 1) they are designed to be efficient within multiple proof systems (e.g. Groth16, Plonk, etc.), 2) they contain dedicated functions optimised for specific applications (namely Merkle tree hashing and general purpose hashing), 3) they have highly competitive performance e.g. about a factor of 2 improvement over Poseidon and Rescue in terms of R1CS constraints, a 21%-35% Plonk constraint reduction over a highly optimized Poseidon implementation, as well as competitive native performance, running between two and three times faster than Rescue, depending on the field size. On the theoretical side, Anemoi pushes further the frontier in understanding the design principles that are truly entailed by arithmetization-orientation. In particular, we identify and exploit a previously unknown relationship between CCZ-equivalence and arithmetization-orientation. In addition, we propose two new standalone components that can be easily reused in new designs. One is a new S-box called Flystel, based on the well-studied butterfly structure, and the second is Jive -- a new mode of operation, inspired by the ``Latin dance'' symmetric algorithms (Salsa, ChaCha and derivatives). Our design is a conservative one: it uses a very classical Substitution-Permutation Network structure, and our detailed analysis of algebraic attacks highlights can be of independent interest.

Designing symmetric-key primitives for applications in Fully Homomorphic Encryption (FHE) has become important to address the issue of the ciphertext expansion. In such a context, cryptographic primitives with a low-AND-depth decryption circuit are desired. Consequently, quadratic nonlinear functions are commonly used in these primitives, including the well-known $\chi$ function over $\mbb{F}_2^n$ and the power map over a large finite field $\mbb{F}_{p^n}$. In this work, we study the growth of the algebraic degree for an SPN cipher over $\mbb{F}_{2^n}^{\width}$, whose S-box is defined as the combination of a power map $x\mapsto x^{2^d+1}$ and an $\mbb{F}_2$-linearized affine polynomial $x\mapsto c_0+\sum_{i=1}^{w}c_ix^{2^{h_i}}$ where $c_1,\ldots,c_w\neq0$. Specifically, motivated by the fact that the original coefficient grouping technique published at EUROCRYPT 2023 becomes less efficient for $w>1$, we develop a variant technique that can efficiently work for arbitrary $w$. With this new technique to study the upper bound of the algebraic degree, we answer the following questions from a theoretic perspective: \begin{enumerate} \item can the algebraic degree increase exponentially when $w=1$? \item what is the influence of $w$, $d$ and $(h_1,\ldots,h_w)$ on the growth of the algebraic degree? \end{enumerate} Based on this, we show (i) how to efficiently find $(h_1,\ldots,h_w)$ to achieve the exponential growth of the algebraic degree and (ii) how to efficiently compute the upper bound of the algebraic degree for arbitrary $(h_1,\ldots,h_w)$. Therefore, we expect that these results can further advance the understanding of the design and analysis of such primitives.

Recent advanced Zero-Knowledge protocols, along with other high-level constructions such as Multi-Party Computations (MPC), have highlighted the need for a new type of symmetric primitives that are not optimized for speed on the usual platforms (desktop computers, servers, microcontrollers, RFID tags...), but for their ability to be implemented using arithmetic circuits.Several primitives have already been proposed to satisfy this need. In order to enable an efficient arithmetization, they operate over large finite fields, and use round functions that can be modelled using low degree equations. The impact of these properties on their security remains to be completely assessed. In particular, algebraic attacks relying on polynomial root-finding become extremely relevant. Such attacks work by writing the cryptanalysis as systems of polynomial equations over the large field, and solving them with off-the-shelf tools (SageMath, NTL, Magma, . . . ).The need for further analysis of these new designs has been recently highlighted by the Ethereum Foundation, as it issued bounties for successful attacks against round-reduced versions of several of them.In this paper, we show that the security analysis performed by the designers (or challenge authors) of four such primitives is too optimistic, and that it is possible to improve algebraic attacks using insights gathered from a careful study of the round function.First, we show that univariate polynomial root-finding can be of great relevance n practice, as it allows us to solve many of the Ethereum Foundation’s challenges on Feistel–MiMC. Second, we introduce a trick to essentially shave off two full rounds at little to no cost for Substitution-Permutation Networks (SPN). This can be combined with univariate (resp. multivariate) root-finding, which allowed to solve some challenges for Poseidon (resp. Rescue–Prime). Finally, we also find an alternative way to set up a system of equations to attack Ciminion, leading to much faster attacks than expected by the designers.