The number of boolean functions with multiplicative complexity 2

The multiplicative complexity of a Boolean function is the minimum number of AND gates (i.e., multiplications) that are sufficient to represent the function over the basis {AND, XOR, NOT}. The multiplicative complexity measure plays a crucial role in cryptography-related applications. In fact, the minimization of the number of AND gates is important for high-level cryptography protocols such as secure multiparty computation, where processing AND gates is more expensive than processing XOR gates. Moreover, it is an indicator of the degree of vulnerability of the circuit, as a small number of AND gates corresponds to a high vulnerability to algebraic attacks. In this paper we study a particular structure regularity of Boolean functions, called autosymmetry, and exploit it to decrease the number of ANDs in XOR-AND Graphs (XAGs), i.e., Boolean networks composed by ANDs, XORs, and inverters. The interest in autosymmetric functions is motivated by the fact that a considerable amount of standard Boolean functions of practical interest presents this regularity; indeed, about 24% of the functions in the classical ESPRESSO benchmark suite have at least one autosymmetric output. The experimental results validate the proposed approach.

In international nuclear safeguards, the International Atomic Energy Agency (IAEA) is tasked with inspecting and verifying nuclear facilities and their activities. Data analytics and machine learning to support inspections require large amounts of data that nuclear facility operators may consider proprietary or sensitive, so the IAEA may not have full access. Allowing computation over private data without compromising its security therefore has value for safeguards inspections and analysis. Privacy-preserving machine learning (PPML) consists of security-focused techniques that allow data analytics and machine learning algorithms to run on sensitive data without revealing it. This includes ideas like homomorphic encryption (HE), secure multiparty computation (SMPC), and secure enclaves. HE allows algorithms and mathematical operations to be conducted directly on the encrypted data instead of first decrypting it. With SMPC, multiple entities collaboratively compute over distributed data such that no party is able to directly view any others’ original data. Secure enclaves allow computation to take place in a separate and heavily blocked-off section of a CPU. Techniques like these allow for several potential use cases in which the security of data is essential. With SMPC, machine learning models can be trained over the input data from multiple entities, resulting in a model that all users can benefit from without leaking the input data from any particular entity. With SMPC or a zero-knowledge proof (ZKP), an algorithm returning some single answer or truth value can be run on someone else’s data without ever needing to see that data, potentially allowing for verification or proof of some underlying question. HE can allow for outsourcing computation on data to a hostile or untrusted environment. Although most of the research in this field resides within the health and financial domains, tools from PPML may have similar applications in nuclear safeguards. Allowing the IAEA to compute over proprietary information, such as process models and raw sensor data using PPML techniques, provides the baseline for running complex analytics without needing direct unencrypted access to the underlying data, maintaining its privacy. Important limitations to consider for these techniques include the efficiency and level of security required. The security of HE and SMPC come at the cost of speed—the significant amount of overhead means that algorithms implemented in these protocols and encryption schemes are slower than when run on plaintext. Additionally, several important parameters determine what techniques or protocols are used based on the security requirements. SMPC protocols may need to be selected for resistance against a party that attempts to deviate from the protocol to distort the result or gain access to additional information, and a protocol secure against these attacks may further increase the overhead of the algorithm.

Multiplicative complexity of vector valued Boolean functions

Password-based authentication systems are vulnerable to a variety of security risks, such as phishing, credential theft, and user fatigue due to complex password requirements. This paper introduces a novel passwordless authentication framework that leverages advanced cryptographic techniques, including Zero-Knowledge Proofs (ZKP), Secure Multi-Party Computation (SMPC), and Homomorphic Encryption to enhance security, privacy, and user experience. The proposed system eliminates the need for traditional passwords by utilizing biometric data to generate cryptographic keys, ensuring that sensitive information remains secure. The architecture is composed of three primary components: the client device, the authentication server, and the key management system (KMS). The client device captures biometric data and transforms it into cryptographic keys using SMPC, while the server verifies the authentication using ZKP and establishes secure communication channels via Diffie-Hellman key exchange. The KMS handles key generation, storage, and rotation to ensure secure communication. Evaluation results show that the system is highly resistant to common attack vectors such as replay and man-in-the-middle attacks, with a 0% attack success rate. Performance analysis reveals an average authentication time of 180 ms, which is 10% faster than WebAuthn.

The multiplicative complexity of an S-box over a finite field is the minimum number of multiplications needed to implement the S-box as an arithmetic circuit. In this paper we fully characterize bijective S-boxes with multiplicative complexity 1 up to affine equivalence over any finite field. We show that under affine equivalence in odd characteristic there are two classes of bijective functions and in even characteristic there are three classes of bijective functions with multiplicative complexity 1. Moreover, in (Jeon et al., Cryptogr. Commun., 14(4), 849-874 (2022)) A-boxes where introduced to lower bound the differential uniformity of an S-box over F2n\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\mathbb {F}_{2}^{n}$$\\end{document} via its multiplicative complexity. We generalize this concept to arbitrary finite fields. In particular, we show that the differential uniformity of a (n, m)-S-box over Fq\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\mathbb {F}_{q}$$\\end{document} is at least qn-l\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$q^{n - l}$$\\end{document}, where ⌊n-12⌋+l\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\lfloor \\frac{n - 1}{2} \\rfloor + l$$\\end{document} is the multiplicative complexity of the S-box.

Motivated by new applications such as secure Multi-Party Computation (MPC), Fully Homomorphic Encryption (FHE), and Zero-Knowledge proofs (ZK), many MPC-, FHE- and ZK-friendly symmetric-key primitives that minimize the< number of multiplications over Fp for a large prime p have been recently proposed in the literature. These symmetric primitives are usually defined via invertible functions, including (i) Feistel and Lai-Massey schemes and (ii) SPN constructions instantiated with invertible non-linear S-Boxes. However, the “invertibility” property is actually never required in any of the mentioned applications.In this paper, we discuss the possibility to set up MPC-/FHE-/ZK-friendly symmetric primitives instantiated with non-invertible bounded surjective functions. In contrast to one-to-one functions, each output of a l-bounded surjective function admits at most l pre-images. The simplest example is the square map x → x2 over Fp for a prime p ≥ 3, which is (obviously) 2-bounded surjective. When working over Fnp for n ≥ 2, we set up bounded surjective functions by re-considering the recent results proposed by Grassi, Onofri, Pedicini and Sozzi at FSE/ToSC 2022 as starting points. Given a quadratic local map F : Fmp → Fp for m ∈ {1, 2, 3}, they proved that the shift-invariant non-linear function over Fnp defined as SF (x0, x1, . . . , xn−1) = y0∥y1∥ . . . ∥yn−1 where yi := F(xi, xi+1) is never invertible for any n ≥ 2 · m − 1. Here, we prove that • the quadratic function F : Fmp → Fp for m ∈ {1, 2} that minimizes the probability of having a collision for SF over Fnp is of the form F(x0, x1) = x20 + x1 (or equivalent);• the function SF over Fnp defined as before via F(x0, x1) = x20 +x1 (or equivalent) is 2n-bounded surjective.As concrete applications, we propose modified versions of the MPC-friendly schemes MiMC, HadesMiMC, and (partially of) Hydra, and of the FHE-friendly schemes Masta, Pasta, and Rubato. By instantiating them with the bounded surjective quadratic functions proposed in this paper, we are able to improve the security and/or the performances in the target applications/protocols.

The multiplicative complexity of a Boolean function f is defined as the minimum number of binary conjunction (AND) gates required to construct a circuit representing f, when only exclusive-or, conjunction and negation gates may be used. This article explores in detail the multiplicative complexity of symmetric Boolean functions. New techniques that allow such exploration are introduced. They are powerful enough to give exact multiplicative complexities for several classes of symmetric functions. In particular, the multiplicative complexity of computing the Hamming weight of n bits is shown to be exactly n−Hℕ(n), where Hℕ(n) is the Hamming weight of the binary representation of n. We also show a close relationship between the complexity of symmetric functions and fractals derived from the parity of binomial coefficients.

It is established that secure computation can be achieved by using a deck of physical cards. Almost all existing card-based protocols are based on a specific deck of cards. In this study, we design card-based protocols that are executable using any deck of cards (e.g., playing cards, UNO, and trading cards). Specifically, we construct a card-based protocol for any Boolean function based on any deck of cards. As corollaries of our result, a standard deck of playing cards (having 52 cards) enables secure computation of any 22-variable Boolean function, and UNO (having 112 cards) enables secure computation of any 53-variable Boolean function.

Two Boolean functions are affine equivalent if one can be obtained from the other by applying an affine transformation to the input variables. For a long time, there have been efforts to investigate the affine equivalence of Boolean functions. Due to the complexity of the general problem, only affine equivalence under certain groups of permutations is usually considered. Boolean functions which are invariant under the action of cyclic rotation of the input variables are known as rotation symmetric (RS) Boolean functions. Due to their speed of computation and the prospect of being good cryptographic Boolean functions, this class of Boolean functions has received a lot of attention from cryptographic researchers. In this paper, we study affine equivalence for the simplest rotation symmetric Boolean functions, called MRS functions, which are generated by the cyclic permutations of a single monomial. Using Pólya’s enumeration theorem, we compute the number of equivalence classes, under certain large groups of permutations, for these MRS functions in any number

Zero Knowledge Proofs (ZKPs) have emerged as transformative cryptographic primitives, enabling a wide variety of modern privacy-preserving applications across various domains. This paper presents substantial advancements in contemporary ZKPs, exploring the latest trends in ZKP schemes, novel applications, and scalable ZKP-based systems. We provide an in-depth analysis of state-of-the-art ZKP structures, including zk-SNARKs, zk-STARKs, and the more recent zk-Rollup technologies. We examine the unique properties and use cases of these techniques, highlighting their potential to enhance privacy, security, and trust in digital systems. Our research into zk-Rollups demonstrates significant improvements in transaction throughput and gas efficiency, paving the way for the extensive deployment of modern privacy-preserving solutions. Furthermore, we showcase several innovative applications of ZKPs, such as privacy-preserving decentralized finance (DeFi) protocols, anonymous credentials, and secure multi-party computation. These use cases illustrate the transformative potential of advanced ZKPs to improve privacy and security across a range of digital domains. To foster wider adoption of modern ZKPs, we have developed and opensourced a collection of advanced tools and libraries that simplify the implementation of ZKP-based solutions. We also offer practical guidance and best practices for developers and researchers working in this field, aiming to accelerate the development and real-world impact of modern zero-knowledge proof systems.

Boolean functions with maximum algebraic immunity have been considered as one class of cryptographically significant functions. It is known that Boolean functions on odd variables have maximum algebraic immunity if and only if a correlative matrix has column full rank, and Boolean functions on even variables have maximum algebraic immunity if and only if two correlative matrices have column full rank. Recently, a smaller matrix was used in the odd case. We find that one or two smaller matrices can be used in the even case and consequently present several sufficient and necessary conditions for Boolean functions with maximum algebraic immunity. This result advances the ability to identify whether Boolean functions on even variables achieve maximum algebraic immunity. We also present a construction algorithm for n-variable Boolean functions with maximum algebraic immunity, specially with the Hamming weights of \( \sum {_{i = 0}^{\left\lceil {\frac{n} {2}} \right\rceil - 1} } \left( {\begin{array}{*{20}c} n \\ i \\ \end{array} } \right) \). It is easily realized for not too large n and helps construct balanced Boolean functions with maximum algebraic immunity on even variables. Furthermore, we present a sufficient and necessary condition for balanced Boolean functions to achieve maximum algebraic immunity and optimum algebraic degree, and modify the construction algorithm to construct Boolean functions on odd variables with maximum algebraic immunity, optimum algebraic degree and high nonlinearity.

We present a general construction of a zero-knowledge proof for an NP relation R(x,w) which only makes a black-box use of a secure protocol for a related multi-partyfunctionality f. The latter protocol is only required to be secure against a small number of honest but curious players. As an application, we can translate previous results on the efficiency of secure multiparty computation to the domain of zero-knowledge, improving over previous constructions of efficient zero-knowledge proofs. In particular, if verifying R on a witness of length m can be done by a circuit C of size s, and assuming one-way functions exist, we get the following types of zero-knowledge proof protocols.Approaching the witness length. If C has constant depth over ∧,∨,⊕, - gates of unbounded fan-in, we get a zero-knowledge protocol with communication complexity m·poly(k)·polylog(s), where k is a security parameter. Such a protocol can be implemented in either the standard interactive model or, following a trusted setup, in a non-interactive model.Constant-rate zero-knowledge. For an arbitrary circuit C of size s and a bounded fan-in, we geta zero-knowledge protocol with communication complexity O(s)+poly(k). Thus, for large circuits, the ratio between the communication complexity and the circuit size approaches a constant. This improves over the O(ks) complexity of the best previous protocols.

The rapid advancement of digital services and online interactions has highlighted the need for secure, user-centric identity management systems. Traditional identity solutions, often centralized and dependent on trusted third parties, pose challenges related to privacy, security, and control over personal data. Distributed Ledger Technology (DLT), particularly blockchain, offers a promising solution for decentralized identity management by enabling self-sovereign identities (SSI). Through the use of decentralized identifiers (DIDs) and verifiable credentials (VCs), DLT allows individuals to maintain full control over their personal information, eliminating the need for intermediaries while ensuring data integrity and privacy. This paper explores the key principles of DLT-based decentralized identity management, discussing its potential to enhance privacy, security, and interoperability in digital ecosystems. We examine the various technical frameworks, challenges, and standards in the field, with a focus on the integration of DLT with emerging technologies such as zero-knowledge proofs (ZKPs) and secure multiparty computation (SMPC). Additionally, we evaluate real-world use cases, from financial services to healthcare, and the role of regulatory frameworks in shaping the future of decentralized identity systems. Ultimately, DLT presents a paradigm shift in identity management, offering scalable, transparent, and trusted solutions for the digital age.

Distributed networks remarkably enhance the convenience of network connectivity. How to achieve efficient cooperative computation while preserving data privacy is a challenge in the scenario of distributed networks. Secure computation, as the key technology of information security and privacy protection in the distributed networks, attracts more and more attention. In the paper, we develop the protocols of secure two-party computation in the presence of malicious adversaries which are constructed with homomorphic probabilistic cryptosystem, and propose four honest-verifier zero-knowledge proof protocols to detect two cheating behaviours of the malicious adversary. The proposed protocols are more targeted than the existing work. The analysis shows that the proposed protocols are complete, sound and zero-knowledge. As an application, we show how to use our protocols in a secure two-party protocol to detect cheating, which can make it secure in the presence of malicious adversaries.

To tackle emerging security and privacy concerns in consortium blockchain applications, particularly in handling sensitive identity information and transaction data, a novel privacy-preserving framework is proposed. The scheme leverages advanced technologies such as post-quantum cryptography, multi-party computation (MPC), and fully homomorphic encryption (FHE) to enhance security and efficiency. Firstly, a quantum-resistant blind signature mechanism is designed using lattice-based cryptography to mitigate centralization issues and strengthen security against quantum attacks. Secondly, a regulatory-compliant hierarchical encryption model is developed using fully homomorphic encryption, enabling fine-grained access control and data integrity verification without decrypting sensitive data. Additionally, zero-knowledge succinct non-interactive arguments of knowledge (zk-SNARKs) are integrated to ensure privacy while allowing verifiable computation. Experimental evaluations demonstrate that the proposed scheme achieves high encryption efficiency, reduced computational overhead during encryption/decryption, and strong resistance to malicious activities such as tampering, eavesdropping, and replay attacks