International Association
for Cryptologic Research

Non-interactive zero-knowledge (NIZK) arguments allow a prover to convince a verifier about the truthfulness of an NP-statement by sending just one message, without disclosing any additional information. In several practical scenarios, the Fiat-Shamir transform is used to convert an efficient constant-round public-coin honest-verifier zero-knowledge proof system into an efficient NIZK argument system. This approach is provably secure in the random oracle model, crucially requires the programmability of the random oracle and extraction works through rewinds. The works of Lindell [TCC 2015] and Ciampi et al. [TCC 2016] proposed efficient NIZK arguments with non-programmable random oracles along with a programmable common reference string. In this work we show an efficient NIZK argument with straight-line simulation and extraction that relies on features that alone are insufficient to construct NIZK arguments (regardless of efficiency). More specifically we consider the notion of quasi-polynomial time simulation proposed by Pass in [EUROCRYPT 2003] and combine it with simulation and extraction with non-programmable random oracles thus obtaining a NIZK argument of knowledge where neither the zero-knowledge simulator, nor the argument of knowledge extractor needs to program the random oracle. Still, both the simulator and the extractor are straight-line. Our construction uses as a building block a modification of the Fischlin’s transform [CRYPTO 2005] and combines it with the concept of dense puzzles introduced by Baldimtsi et al. [ASIACRYPT 2016]. We also argue that our NIZK argument system inherits the efficiency features of Fischlin’s transform, which represents the main advantage of Fischlin’s protocol over existing schemes.

Falcon is one of post-quantum signature schemes selected by NIST for standardization. With the deployment underway, its implementation security is of great importance. In this work, we focus on the side-channel security of Falcon and our contributions are threefold.

First, by exploiting the symplecticity of NTRU and a recent decoding technique, we dramatically improve the key recovery using power leakages within Falcon Gaussian samplers. Compared to the state of the art (Zhang, Lin, Yu and Wang, EUROCRYPT 2023), the amount of traces required by our attack for a full key recovery is reduced by at least 85%.

Secondly, we present a complete power analysis for two exposed power leakages within Falcon’s integer Gaussian sampler. We identify new sources of these leakages, which have not been identified by previous works, and conduct detailed security evaluations within the reference implementation of Falcon on Chipwhisperer.

Thirdly, we propose effective and easy-to-implement countermeasures against both two leakages to protect the whole Falcon’s integer Gaussian sampler. Configured with our countermeasures, we provide security evaluations on Chipwhisperer and report performance of protected implementation. Experimental results highlight that our countermeasures admit a practical trade-off between effciency and side-channel security.

There is a heavy preference towards instantiating BGV and BFV homomorphic encryption schemes where the cyclotomic order $m$ is a power of two, as this admits highly efficient fast Fourier transformations. Field Instruction Multiple Data (FIMD) was introduced to increase packing capacity in the case of small primes and improve amortised performance, using reverse multiplication-friendly embeddings (RMFEs) to encode more data into each SIMD slot. However, FIMD currently does not admit bootstrapping.

In this work, we achieve bootstrapping for RMFE-packed ciphertexts with low capacity loss. We first adapt the digit extraction algorithm to work over RMFE-packed ciphertexts, by applying the recode map after every evaluation of the lifting polynomial. This allows us to follow the blueprint of thin bootstrapping, performing digit extraction on a single ciphertext. To achieve the low capacity loss, we introduce correction maps to the Halevi-Shoup digit extraction algorithm, to remove all but the final recode of RMFE digit extraction.

We implement several workflows for bootstrapping RMFE-packed ciphertexts in HElib, and benchmark them against thin bootstrapping for $m=32768$. Our experiments show that the basic strategy of recoding multiple times in digit extraction yield better data packing, but result in very low remaining capacity and latencies of up to hundreds of seconds. On the other hand, using correction maps gives up to $6$ additional multiplicative depth and brings latencies often below $10$ seconds, at the cost of lower packing capacity.

We study efficient public randomness generation protocols in the PASSO (PArties Speak Sequentially Once) model for multi-party computation (MPC). PASSO is a variation of traditional MPC where $n$ parties are executed in sequence and each party ``speaks'' only once, broadcasting and sending secret messages only to parties further down the line. Prior results in this setting include information-theoretic protocols in which the computational complexity scales exponentially with the number of corruptions $t$ (CRYPTO 2022), as well as more efficient computationally-secure protocols either assuming a trusted setup phase or DDH (FC 2024). Moreover, these works only consider security against static adversaries.

In this work, we focus on computational security against adaptive adversaries and from minimal assumptions, and improve on the works mentioned above in several ways:

- Assuming the existence of non-interactive perfectly binding commitments, we design protocols with $n=3t+1$ or $n=4t$ parties that are efficient and secure whenever $t$ is small compared to the security parameter $\lambda$ (e.g., $t$ is constant). This improves the resiliency of all previous protocols, even those requiring a trusted setup. It also shows that $n=4$ parties are necessary and sufficient for $t=1$ corruptions in the computational setting, while $n=5$ parties are required for information-theoretic security.

- Under the same assumption, we design protocols with $n=4t+2$ or $n=5t+2$ parties (depending on the adversarial network model) which are efficient whenever $t=poly(\lambda)$. This improves on the existing DDH-based protocol both in terms of resiliency and the underlying assumptions. - We design efficient protocols with $n=5t+3$ or $n=6t+3$ parties (depending on the adversarial network model) assuming the existence of one-way functions.

We complement these results by studying lower bounds for randomness generation protocols in the computational setting.

Existing secret management techniques demand users memorize complex passwords, store convoluted recovery phrases, or place their trust in a specific service or hardware provider. We have designed a novel protocol that combines existing cryptographic techniques to eliminate these complications and reduce user complexity to recalling a short PIN. Our protocol specifically focuses on a distributed approach to secret storage that leverages Oblivious Pseudorandom Functions (OPRFs) and a Secret-Sharing Scheme (SSS) combined with self-destructing secrets to minimize the trust placed in any singular server. Additionally, our approach allows for servers distributed across organizations, eliminating the need to trust a singular service operator. We have built an open-source implementation of the client and server sides of this new protocol, the latter of which has variants for running on commodity hardware and secure hardware.

With the growing emphasis on data privacy, secure multi-party computation has garnered significant attention for its strong security guarantees in developing privacy-preserving machine learning (PPML) schemes. However, only a few works address scenarios with a large number of participants. The state of the art by Liu et al. (LXY24, USENIX Security'24) first achieves a practical PPML protocol for up to 63 parties but is constrained to semi-honest security. Although naive extensions to the malicious setting are possible, they would introduce significant overhead. In this paper, we propose Helix, a scalable framework for maliciously secure PPML in the honest majority setting, aiming to enhance both the scalability and practicality of maliciously secure protocols. In particular, we report a privacy leakage issue in LXY24 during prefix OR operations and introduce a round-optimized alternative based on a single-round vectorized three-layer multiplication protocol. Additionally, by exploiting reusability properties within the computation process, we propose lightweight compression protocols that substantially improve the efficiency of multiplication verification. We also develop a batch check protocol to reduce the computational complexity of revealing operations in the malicious setting. For 63-party neural network inference, compared to the semi-honest LXY24, Helix is only 1.9$\times$ (1.1$\times$) slower in the online phase and 1.2$\times$ (1.1$\times$) slower in preprocessing under LAN (WAN) in the best case.

Existing fully homomorphic encryption (FHE) schemes primarily support a plaintext space defined over a relatively small prime. However, in some important applications of FHE one needs arithmetic over a large prescribed prime. In this paper we construct a new FHE system that is specifically designed for this purpose. Our system composes three layers of residue systems to enable much better performance than was previously possible. Our experiments show that for arithmetic modulo a 256-bit integer, when compared to the TFHE-rs implementation of 256-bit arithmetic, our new system achieves a factor of a thousand better multiplication throughput and a factor of ten better latency. Moreover, for a 2048-bit prime modulus we achieve far better performance than was previously possible.

Proxy re-encryption (PRE) has been regarded as an effective cryptographic primitive in data sharing systems with distributed proxies. However, no literature considers the honesty of data owners, which is critical in the age of big data. In this paper, we fill the gap by introducing a new proxy re-encryption scheme, called publicly verifiable threshold PRE (PVTPRE). Briefly speaking, we innovatively apply a slightly modified publicly verifiable secret sharing (PVSS) scheme to distribute the re-encryption keys to multiple proxies. Consequently, we achieve publicly verifiability of data owners non-interactively. Then, the correctness of data users in decryption and public verifiability of proxies in re-encryption are guaranteed seamlessly through execution of the PVSS reconstruction algorithms. We further prove that PVTPRE satisfies IND-CPA security. Besides, we put forward a privacy-preserving data rights confirmation framework by providing clear principles for data ownership and usage, based on the PVTPRE scheme and blockchain. Blockchain plays the role of data bank and smart contract engine, providing reliable storage and verification for all framework. To our knowledge, we are the first to systematically investigate data rights confirmation considering privacy as well as public verifiability, addressing the growing need for robust mechanisms to protect data rights and ensure transparency. Finally, we conduct comprehensive experiments to illustrate the correctness, feasibility and effectiveness. The experimental results show that our PVTPRE outperforms other PREs in many aspects.

Generalized secret sharing (GSS), which can offer more flexibility by accommodating diverse access structures and conditions, has been under-explored in distributed computing over the past decades. To address the gaps, we propose the publicly verifiable generalized secret sharing (PVGSS) scheme, enhancing the applicability of GSS in transparent systems. Public verifiability is a crucial property to gain trustworthiness for decentralized systems like blockchain. We begin by introducing two GSS constructions, one based on Shamir's secret sharing and the other on the linear secret sharing scheme (LSSS). Next, we present PVGSS schemes that combine GSS with non-interactive zero-knowledge (NIZK) proofs. Further, we construct a decentralized exchange (DEX) based on PVGSS scheme, where any users can participate in exchanges and engage in arbitrage. Specifically, users can fairly swap ERC-20 tokens with passive watchers, who earn profits by providing arbitration services. The critical property of "fairness" required by the DEX is ensured through a sophisticated access structure, supported by the PVGSS scheme. We provide a comprehensive evaluation on the performance of the PVGSS schemes and the monetary costs for users in the DEX. The results demonstrate the feasibility and practicality of this approach in real-world applications.

A key encapsulation mechanism (KEM) allows two parties to establish a shared secret key using only public communication. For post-quantum KEMs, the most widespread approach is to design a passively secure public-key encryption (PKE) scheme and then apply the Fujisaki–Okamoto (FO) transform that turns any such PKE scheme into an IND-CCA secure KEM. While the base security requirement for KEMs is typically IND-CCA security, adversaries in practice can sometimes observe and attack many public keys and/or ciphertexts, which is referred to as multi-challenge security. FO does not necessarily guarantee multi-challenge security: for example, FrodoKEM, a Round 3 alternate in NIST’s post-quantum project, used FO to achieve IND-CCA security, but was subsequently shown to be vulnerable to attackers that can target multiple ciphertexts. To avert this multi-ciphertext attack, the FrodoKEM team added a salt to the encapsulation procedure and proved that this does not degrade (single-ciphertext) IND-CCA security. The formal analysis of whether this indeed averts multi-ciphertext attacks, however, was left open, which we address in this work.

Firstly, we formalize FrodoKEM's approach as a new variant of the FO transform, called the salted FO transform. Secondly, we give tight reductions from multi-challenge security of the resulting KEM to multi-challenge security of the underlying public key encryption scheme, in both the random oracle model (ROM) and the quantum-accessible ROM (QROM). Together these results justify the multi-ciphertext security of the salted FrodoKEM scheme, and can also be used generically by other schemes requiring multi-ciphertext security.

The fundamental assumption in $t$-out-of-$n$ threshold encryption is that the adversary can only corrupt less than $t$ parties. Unfortunately, it may be unfounded in practical scenarios where shareholders could be incentivized to collude. Boneh, Partap, and Rotem (Crypto'24) recently addressed the setting where $t$ or more shareholders work together to decrypt illegally. Inspired by the well-established notion of traitor tracing in broadcast encryption, they added a traceability mechanism that guarantees identifying at least one of the colluders. They provide several constructions that enable traceability, all of which require a trusted dealer to distribute the secret shares. While the trusted dealer can be replaced with a DKG for conventional threshold encryption, it is unclear how to do so without compromising traceability. As thresholdizing is meant to mitigate a single point of failure, a natural question that remains is: Can we construct an efficient traceable threshold encryption scheme that does not rely on a trusted party to distribute the secret shares? In this paper, we achieve two dealerless traceable threshold encryption constructions with different merits by extending the PLBE primitive of Boneh et al. (Eurocrypt'06) and combining it with the silent setup threshold encryption construction of Garg et al. (Crypto'24). Our first construction achieves an amortized ciphertext of size $O(1)$ (for $O(n)$ ciphertexts). Our second construction achieves constant ciphertext size even in the worst case but requires a less efficient preprocessing phase as a tradeoff. Both our constructions enjoy a constant secret key size and do not require any interaction between the parties. An additional restriction in the constructions of Boneh et al. is that they can only guarantee to find at least one colluder, leaving techniques to identify more traitors as an open problem. In this paper, we take a first step towards solving this question by formalizing a technique and applying it to our first construction. Namely, our first construction enables tracing $t$ traitors.

A recent work by Boneh, Partap, and Rotem [Crypto'24] introduced the concept of traceable threshold encryption, in that if $t$ or more parties collude to construct a decryption box, which performs decryptions, then at least one party's identity can be traced by making a few black-box queries to the box. This has important applications, e.g., in blockchain mempool privacy, where collusion yields high financial gain through MEVs without any consequence - the possibility of tracing discourages collusion. Nevertheless, their definitions leave room for exploitation as they only achieve CPA security and do not consider inconsistency in decryption via different participating sets.

This paper proposes stronger definitions of traceable threshold encryption, which supports CCA-security and consistency. Our main approach considers identity-based variants of traceable encryption (which we also define). It converts that to a CCA-secure construction, adapting two generic transformations, first using a one-time signature and then a fingerprinting code. We put forward two efficient instantiations of our identity-based scheme with different merits: our first construction is based on Boneh-Franklin IBE [Crypto'01] and has constant size ciphertexts but quadratic size public keys - this is proven secure based on XDH and BDDH. Our second construction is based on Boneh-Boyen IBE [Eurocrypt'04]. It supports both constant-size ciphertexts and constant-size public keys - this is proven secure based on a variant of the uber assumption over bilinear pairings. Our concrete analysis shows that the first construction's ciphertext is much (~6x) smaller than the second construction. Finally, we extend the definitions to support consistency and achieve it by adjoining an efficient, non-interactive proof of correct encryption.

Updatable public-key encryption (UPKE) allows anyone to update a public key while simultaneously producing an update token, given which the secret key holder could consistently update the secret key. Furthermore, ciphertexts encrypted under the old public key remain secure even if the updated secret key is leaked -- a property much desired in secure messaging. All existing lattice-based constructions of UPKE update keys by a noisy linear shift. As the noise accumulates, these schemes either require super-polynomial-size moduli or an a priori bounded number of updates to maintain decryption correctness.

Inspired by recent works on cryptography based on the lattice isomorphism problem, we propose an alternative way to update keys in lattice-based UPKE. Instead of shifting, we rotate them. As rotations do not induce norm growth, our construction supports an unbounded number of updates with a polynomial-size modulus. The security of our scheme is based on the LWE assumption over hollow matrices -- matrices which generate linear codes with non-trivial hull -- and the hardness of permutation code equivalence. Along the way, we also show that LWE over hollow matrices is as hard as LWE over uniform matrices, and that a leftover hash lemma holds for hollow matrices.

We propose a new method to construct a public-key encryption scheme, where one can homomorphically transform a ciphertext encrypted under a key $\mathbf{x}$ into a ciphertext under $(P, P(\mathbf{x}))$, for any polynomial-time RAM program $P: \mathbf{x} \mapsto \mathbf{y}$ with runtime $T$ and memory $L$. Combined with other lattice techniques, this allows us to construct: 1) Succinct-randomised encodings from RAM programs with encoder complexity $(|\mathbf{x}| + |\mathbf{y}|)\cdot \text{poly}(\log T, \log L)$ and rate-1 encodings. 2) Laconic function evaluation for RAM programs, with encoder runtime bounded by $(|\mathbf{x}| + |\mathbf{y}|)\cdot\text{poly}(\log T, \log L)$ and rate-1 encodings. 3) Key-policy attribute-based encryption for RAM programs, with ciphertexts of size $O(T)$. The same scheme can be converted to the register setting, obtaining linear CRS size in the number of parties.

All of our schemes rely on the hardness of the \emph{decomposed learning with errors} (LWE) problem, along with other standard computational assumptions on lattices. The decomposed LWE problem can be interpreted as postulating the circular-security of a natural lattice-based public-key encryption scheme. To gain confidence in the assumption, we show that it is implied by the hardness of the succinct LWE problem of Wee (CRYPTO'24).

Constant-time (CT) is a popular programming discipline to protect cryptographic libraries against micro-architectural timing attacks. One appeal of the CT discipline lies in its conceptual simplicity: a program is CT iff it has no secret-dependent data-flow, control-flow or variable-timing operation. Thanks to its simplicity, the CT discipline is supported by dozens of analysis tools. However, a recent user study demonstrates that these tools are seldom used due to poor usability and maintainability (Jancar et al. IEEE SP 2022).

In this paper, we introduce CT-LLVM, a CT analysis tool designed for usability, maintainability and automatic large-scale analysis. Concretely, CT-LLVM is packaged as a LLVM plugin and is built as a thin layer on top of two standard LLVM analysis: def-use and alias analysis. Besides confirming known CT violations, we demonstrate the usability and scalability of CT-LLVM by automatically analyzing nine cryptographic libraries. On average, CT-LLVM can automatically and soundly analyze 36% of the functions in these libraries, proving that 61% of them are CT. In addition, the large-scale automatic analysis also reveals new vulnerabilities in these libraries. In the end, we demonstrate that CT-LLVM helps systematically mitigate compiler-introduced CT violations, which has been a long-standing issue in CT analysis.

Leakage-resilient secret sharing schemes are a fundamental building block for secure computation in the presence of leakage. As a result, there is a strong interest in building secret sharing schemes that combine resilience in practical leakage scenarios with potential for efficient computation. In this work, we revisit the inner-product framework, where a secret $y$ is encoded by two vectors $(\omega, y)$, such that their inner product is equal to $y$. So far, the most efficient inner-product masking schemes (in which $\omega$ is public but random) are provably secure with the same security notions (e.g., in the abstract probing model) as additive, Boolean masking, yet at the cost of a slightly more expensive implementation. Hence, their advantage in terms of theoretical security guarantees remains unclear, also raising doubts about their practical relevance. We address this question by showing the leakage resilience of inner-product masking schemes, in the bounded leakage threat model. It depicts well implementation contexts where the physical noise is negligible. In this threat model, we show that if $m$ bits are leaked from the $d$ shares $y$ of the encoding over an $n$-bit field, then with probability at least $1−2^{-\lambda}$ over the choice of $\omega$, the scheme is $O(\sqrt{ 2^{−(d−1)·n+m+2\lambda}})$-leakage resilient. Furthermore, this result holds without assuming independent leakage from the shares, which may be challenging to enforce in practice. We additionally show that in large Mersenne-prime fields, a wise choice of the public coefficients $\omega$ can yield leakage resilience up to $O(n · 2^{−d·n+n+d})$, in the case where one physical bit from each share is revealed to the adversary. The exponential rate of the leakage resilience we put forward significantly improves upon previous bounds in additive masking, where the past literature exhibited a constant exponential rate only.

We propose the notion of succinct oblivious tensor evaluation (OTE), where two parties compute an additive secret sharing of a tensor product of two vectors $\mathbf{x} \otimes \mathbf{y}$, exchanging two simultaneous messages. Crucially, the size of both messages and of the CRS is independent of the dimension of $\mathbf{x}$. We present a construction of OTE with optimal complexity from the standard learning with errors (LWE) problem. Then we show how this new technical tool enables a host of cryptographic primitives, all with security reducible to LWE, such as: 1)Adaptively secure laconic function evaluation for depth-$D$ functions $f:\{0, 1\}^m\rightarrow\{0, 1\}^\ell$ with communication $m+\ell+D\cdot \mathsf{poly}(\lambda)$. 2) A trapdoor hash function for all functions. 3) An (optimally) succinct homomorphic secret sharing for all functions. 4) A rate-$1/2$ laconic oblivious transfer for batch messages, which is best possible. In particular, we obtain the first laconic function evaluation scheme that is adaptively secure from the standard LWE assumption, improving upon Quach, Wee, and Wichs (FOCS 2018). As a key technical ingredient, we introduce a new notion of adaptive lattice encodings, which may be of independent interest.

Multi-signatures allow a set of parties to produce a single signature for a common message by combining their individual signatures. The result can be verified using the aggregated public key that represents the group of signers. Very recent work by Lehmann and Özbay (PKC '24) studied the use of multi-signatures for ad-hoc privacy-preserving group signing, formalizing the notion of multi-signatures with probabilistic yet verifiable key aggregation. Moreover, they proposed new BLS-type multi-signatures, allowing users holding a long-term key pair to engage with different groups, without the aggregated key leaking anything about the corresponding group. This enables key-reuse across different groups in a privacy-preserving way. Unfortunately, their technique cannot be applied to Schnorr-type multi-signatures, preventing state-of-the-art multi-signatures to benefit from those privacy features.

In this work, we revisit the privacy framework from Lehmann and Özbay. Our first contribution is a generic lift that adds privacy to any multi-signature with deterministic key aggregation. As our second contribution, we study two concrete multi-signatures, and give dedicated transforms that take advantage of the underlying structures for improved efficiency. The first one is a slight modification of the popular MuSig2 scheme, achieving the strongest privacy property for free compared to the original scheme. The second is a variant of the lattice-based multi-signature scheme DualMS, making our construction the first post-quantum secure multi-signature for ad-hoc privacy-preserving group signing. The light overhead incurred by the modifications in our DualMS variant still allow us to benefit from the competitiveness of the original scheme.

In Crypto'19, Goyal, Jain, and Sahai (GJS) introduced the elegant notion of *secret-sharing of an NP statement* (NPSS). Roughly speaking, a $t$-out-of-$n$ secret sharing of an NP statement is a reduction that maps an instance-witness pair to $n$ instance-witness pairs such that any subset of $(t-1)$ reveals no information about the original witness, while any subset of $t$ allows full recovery of the original witness. Although the notion was formulated for general $t \leq n$, the only existing construction (due to GJS) applies solely to the case where $t = n$ and provides only computational privacy. In this paper, we further explore NPSS and present the following contributions.

1. **Definition.** We introduce a refined definition of information-theoretically secure NPSS. This notion can be seen as a cryptographic variant of standard NP-reductions and can be compiled into the GJS definition using any one-way function.

2. **Construction.** We construct information-theoretic $t$-out-of-$n$ NPSS for any values of $t\leq n$ with complexity polynomial in $n$. Along the way, we present a new notion of secure multiparty computation that may be of independent interest.

3. **Applications.** Our NPSS framework enables the *non-interactive combination* of $n$ instances of zero-knowledge proofs, where only $t_s$ of them are sound and only $t_z$ are zero-knowledge, provided that $t_s + t_z > n$. Our combiner preserves various desirable properties, such as the succinctness of the proof. Building on this, we establish the following results under the minimal assumption of one-way functions: (i) *Standard NIZK implies NIZK in the Multi-String Model* (Groth and Ostrovsky, J. Cryptology, 2014), where security holds as long as a majority of the $n$ common reference strings were honestly generated. Previously, such a transformation was only known in the common random string model, where the reference string is uniformly distributed. (ii) A *Designated-Prover NIZK in the Multi-String Model*, achieving a strong form of two-round Multi-Verifier Zero-Knowledge in the honest-majority setting. (iii) A *three-round secure multiparty computation protocol* for general functions in the honest-majority setting. The round complexity of this protocol is optimal, resolving a line of research that previously relied on stronger assumptions (Aharonov et al., Eurocrypt'12; Gordon et al., Crypto'15; Ananth et al., Crypto'18; Badrinarayanan et al., Asiacrypt'20; Applebaum et al., TCC'22).

Oblivious pseudorandom functions (OPRFs) are an important primitive in privacy-preserving cryptographic protocols. The growing interest in OPRFs, both in theory and practice, has led to the development of numerous constructions and variations. However, most of these constructions rely on classical assumptions. Potential future quantum attacks may limit the practicality of those OPRFs for real-world applications.

To close this gap, we introduce Leap, a novel OPRF based on heuristic lattice assumptions. Fundamentally, Leap builds upon the Spring [BBL+15] pseudorandom function (PRF), which relies on the learning with rounding assumption, and integrates techniques from multi-party computation, specifically Oblivious Transfer (OT) and Oblivious Linear Evaluation (OLE). With this combination of oblivious protocols, we construct an OPRF that evaluates in less than a millisecond on a modern computer.

Efficiency-wise, our prototype implementation achieves computation times of just 11 microseconds for the client and 750 microseconds for the server, excluding some base OT preprocessing overhead. Moreover, Leap requires an online communication cost of 23 kB per evaluation, where the client only has to send around 380 bytes online. To demonstrate the practical applicability of Leap, we present an efficient private set intersection (PSI) protocol built on top of Leap. This application highlights the potential for the integration of Leap into various privacy-preserving applications: We can compute an unbalanced set intersection with set sizes of 2^24 and 2^15 in under a minute of online time and just over two minutes overall.