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24 September 2023
Yaobin Shen, François-Xavier Standaert, Lei Wang
At CRYPTO'18, Datta et al. proposed nPolyMAC and proved the security up to 2^{2n/3} authentication queries and 2^{n} verification queries. At EUROCRYPT'19, Dutta et al. proposed CWC+ and showed the security up to 2^{2n/3} queries. At FSE'19, Datta et al. proposed PolyMAC and its key-reduced variant 2k-PolyMAC, and showed the security up to 2^{2n/3} queries. This security bound was then improved by Kim et al. (EUROCRYPT'20) and Datta et al (FSE'23) respectively to 2^{3n/4} and in the multi-user setting. At FSE'20, Chakraborti et al. proposed PDM*MAC and 1k-PDM*MAC and showed the security up to 2^{2n/3} queries. Recently, Chen et al. proposed nEHtM_p^+ and showed the security up to 2^{2n/3} queries. In this paper, we show forgery attacks on nPolyMAC, CWC+, PolyMAC, 2k-PolyMAC, PDM*MAC, 1k-PDM*MAC and nEHtM_p^+. Our attacks exploit some vulnerability in the underlying polynomial hash function Poly, and (i) require only one authentication query and one verification query; (ii) are nonce-respecting; (iii) succeed with probability 1. Thus, our attacks disprove the provable high security claims of these schemes. We then revisit their security analyses and identify what went wrong. Finally, we propose two solutions that can restore the beyond-birthday-bound security.
Zhengjun Cao, Lihua Liu
We show that the key agreement scheme [J. Syst. Archit., 131:102698, 2022] fails to keep user anonymity and service provider anonymity, not as claimed. The scheme simply thinks that user anonymity is equivalent to protecting the target user's identity against exposure, while its long-term pseudo-identity can be exposed. We want to clarify that the true anonymity means that an adversary cannot attribute different sessions to different target users, even if the true identifier cannot be retrieved from the exposed pseudo-identifier.
Shiyu Shen, Hao Yang, Wangchen Dai, Lu Zhou, Zhe Liu, Yunlei Zhao
Homomorphic Encryption (HE) enhances data security by facilitating computations on encrypted data, opening new paths for privacy-focused computations. The Brakerski-Fan-Vercauteren (BFV) scheme, a promising HE scheme, raises considerable performance challenges. Graphics Processing Units (GPUs), with considerable parallel processing abilities, have emerged as an effective solution.
In this work, we present an in-depth study focusing on accelerating and comparing BFV variants on GPUs, including Bajard-Eynard-Hasan-Zucca (BEHZ), Halevi-Polyakov-Shoup (HPS), and other recent variants. We introduce a universal framework accommodating all variants, propose optimized BEHZ implementation, and first support HPS variants with large parameter sets on GPUs. Moreover, we devise several optimizations for both low-level arithmetic and high-level operations, including minimizing instructions for modular operations, enhancing hardware utilization for base conversion, implementing efficient reuse strategies, and introducing intra-arithmetic and inner-conversion fusion methods, thus decreasing the overall computational and memory consumption.
Leveraging our framework, we offer comprehensive comparative analyses. Our performance evaluation showcases a marked speed improvement, achieving 31.9× over OpenFHE running on a multi-threaded CPU and 39.7% and 29.9% improvement, respectively, over the state-of-the-art GPU BEHZ implementation. Our implementation of the leveled HPS variant records up to 4× speedup over other variants, positioning it as a highly promising alternative for specific applications.
In this work, we present an in-depth study focusing on accelerating and comparing BFV variants on GPUs, including Bajard-Eynard-Hasan-Zucca (BEHZ), Halevi-Polyakov-Shoup (HPS), and other recent variants. We introduce a universal framework accommodating all variants, propose optimized BEHZ implementation, and first support HPS variants with large parameter sets on GPUs. Moreover, we devise several optimizations for both low-level arithmetic and high-level operations, including minimizing instructions for modular operations, enhancing hardware utilization for base conversion, implementing efficient reuse strategies, and introducing intra-arithmetic and inner-conversion fusion methods, thus decreasing the overall computational and memory consumption.
Leveraging our framework, we offer comprehensive comparative analyses. Our performance evaluation showcases a marked speed improvement, achieving 31.9× over OpenFHE running on a multi-threaded CPU and 39.7% and 29.9% improvement, respectively, over the state-of-the-art GPU BEHZ implementation. Our implementation of the leveled HPS variant records up to 4× speedup over other variants, positioning it as a highly promising alternative for specific applications.
Hao Yang, Shiyu Shen, Siyang Jiang, Lu Zhou, Wangchen Dai, Yunlei Zhao
Homomorphic Encryption (HE) presents a promising solution to securing neural networks for Machine Learning as a Service (MLaaS). Despite its potential, the real-time applicability of current HE-based solutions remains a challenge, and the diversity in network structures often results in inefficient implementations and maintenance. To address these issues, we introduce a unified and compact network structure for real-time inference in convolutional neural networks based on HE. We further propose several optimization strategies, including an innovative compression and encoding technique and rearrangement in the pixel encoding sequence, enabling a highly efficient batched computation and reducing the demand for time-consuming HE operations. To further expedite computation, we propose a GPU acceleration engine to leverage the massive thread-level parallelism to speed up computations. We test our framework with the MNIST, Fashion-MNIST, and CIFAR-10 datasets, demonstrating accuracies of 99.14%, 90.8%, and 61.09%, respectively. Furthermore, our framework maintains a steady processing speed of 0.46 seconds on a single-thread CPU, and a brisk 31.862 milliseconds on an A100 GPU for all datasets. This represents an enhancement in speed more than 3000 times compared to pervious work, paving the way for future explorations in the realm of secure and real-time machine learning applications.
Samuel Coulon, Pengzhou He, Tianyou Bao, Jiafeng Xie
The recently announced National Institute of Standards and Technology (NIST) Post-quantum cryptography (PQC) third-round standardization process has released its candidates to be standardized and Falcon is one of them. On the other hand, however, very few hardware implementation works for Falcon have been released due to its very complicated computation procedure and intensive complexity. With this background, in this paper, we propose an efficient hardware structure to implement residue numeral system (RNS) decomposition within NTRUSolve (a key arithmetic component for key generation of Falcon). In total, we have proposed three stages of coherent interdependent efforts to finish the proposed work. First, we have identified the necessary algorithmic operation related to RNS decomposition. Then, we have innovatively designed a hardware structure to realize these algorithms. Finally, field-programmable gate array (FPGA)-based implementation has been carried out to verify the superior performance of the proposed hardware structure. For instance, the proposed hardware design involves at least 3.91x faster operational time than the software implementation. To the authors' best knowledge, this is the first paper about the hardware acceleration of RNS decomposition for Falcon, and we hope the outcome of this work will facilitate the research in this area.
Aysajan Abidin, Erik Pohle, Bart Preneel
Secure multi-party computation (MPC) enables multiple distrusting parties to compute a function while keeping their respective inputs private. In a threshold implementation of a symmetric primitive, e.g., of a block cipher, each party holds a share of the secret key or of the input block. The output block is computed without reconstructing the secret key. This enables the construction of distributed TPMs or transciphering for secure data transmission in/out of the MPC context.
This paper investigates implementation approaches for the lightweight primitives SKINNY and PHOTON in arithmetic circuits.
For these primitives, we identify arithmetic expressions for the S-box that result in smaller arithmetic circuits compared to the Boolean expressions from the literature.
We validate the optimization using a generic actively secure MPC protocol and obtain 18% faster execution time with 49% less communication data for SKINNY-64-128 and 27% to 74% faster execution time with 49% to 81% less data for PHOTON $P_{100}$ and $P_{288}$.
Furthermore, we find a new set of parameters for the heuristic method of polynomial decomposition, introduced by Coron, Roy and Vivek, specialized for SKINNY's 8-bit S-box. We reduce the multiplicative depth from 9 to 5.
Fernando Virdia
A recent series of works (Hecht, IACR ePrint, 2020–2021) propose to build post-quantum public-key encapsulation, digital signatures, group key agreement and oblivious transfer from "R-propped" variants of the Symmetrical Decomposition and Discrete Logarithm problems for matrix groups over $\mathbb{F}_{2^8}$. We break all four proposals by presenting a linearisation attack on the Symmetrical Decomposition platform, a forgery attack on the signature scheme, and a demonstration of the insecurity of the instances of the Discrete Logarithm Problem used for signatures, group key agreement and oblivious transfer, showing that none of the schemes provides adequate security.
Bala Subramanyan
Amid the landscape of confidential computing, where security and privacy reign supreme, PRIVATON emerges as a pioneering and practical solution to safeguard sensitive data and computations. A verifiable proof of computation model, with one of its variant built upon the dual sandbox strategy, PRIVATON combines Trusted Execution Environment (TEE) technologies with WebAssembly (WASM) runtime environments to establish an ecosystem for privacy-preserving computations. This approach involves fine grained modeling of computations as finite state automatons, guided by verifiable proofs that attest to their unerring execution.
PRIVATON is guided by the profound principles of "least privilege" and "intentional use." Through the former, each computation module's privileges are meticulously constrained, reducing vulnerability vectors. The latter ensures that privileges are allocated explicitly, fostering comprehension and security. This rigorous adherence minimizes privilege misuse and information leakage, bolstering the overall security posture.
At its core, PRIVATON's innovation lies in its comprehensive assurance of data privacy and security. State machine proofs not only attest to the absence of data leakage but also prevent unauthorized data transmission. By providing unassailable proof of computation integrity, PRIVATON shields against code misuse within the system. This proactive stance fortifies its mission to safeguard the sanctity of data, computations, and the privacy of all stakeholders.
Evidenced by its real-world application, PRIVATON has been validated within the cryptocurrency trading ecosystem, where it acts as a distributed and privacy-preserving credit oracle. Its implementation within Credora’s landscape underlines its potential to transform data-centric paradigms, empowering stakeholders with an unshakeable confidence in data security. In a world where data privacy is paramount, PRIVATON stands as a guardian, epitomizing the convergence of technology, security, and trust.
PRIVATON is guided by the profound principles of "least privilege" and "intentional use." Through the former, each computation module's privileges are meticulously constrained, reducing vulnerability vectors. The latter ensures that privileges are allocated explicitly, fostering comprehension and security. This rigorous adherence minimizes privilege misuse and information leakage, bolstering the overall security posture.
At its core, PRIVATON's innovation lies in its comprehensive assurance of data privacy and security. State machine proofs not only attest to the absence of data leakage but also prevent unauthorized data transmission. By providing unassailable proof of computation integrity, PRIVATON shields against code misuse within the system. This proactive stance fortifies its mission to safeguard the sanctity of data, computations, and the privacy of all stakeholders.
Evidenced by its real-world application, PRIVATON has been validated within the cryptocurrency trading ecosystem, where it acts as a distributed and privacy-preserving credit oracle. Its implementation within Credora’s landscape underlines its potential to transform data-centric paradigms, empowering stakeholders with an unshakeable confidence in data security. In a world where data privacy is paramount, PRIVATON stands as a guardian, epitomizing the convergence of technology, security, and trust.
Nina Bindel, Xavier Bonnetain, Marcel Tiepelt, Fernando Virdia
In 2018, Aono et al. (ASIACRYPT 2018) proposed to use quantum backtracking algorithms (Montanaro, TOC 2018; Ambainis and Kokainis, STOC 2017) to speedup lattice point enumeration. Quantum lattice sieving algorithms had already been proposed (Laarhoven et al., PQCRYPTO 2013), being shown to provide an asymptotic speedup over classical counterparts, but also to lose competitivity at relevant dimensions to cryptography if practical considerations on quantum computer architecture were taken into account (Albrecht et al., ASIACRYPT 2020). Aono et al.’s work argued that quantum walk speedups can be applied to lattice enumeration, achieving at least a quadratic asymptotic speedup à la Grover search while not requiring exponential amounts of quantum accessible classical memory, as it is the case for sieving. In this work, we explore how to lower bound the cost of using Aono et al.’s techniques on lattice enumeration with extreme cylinder pruning assuming a limit to the maximum depth that a quantum computation can achieve without decohering, with the objective of better understanding the practical applicability of quantum backtracking in lattice cryptanalysis.
Nilanjan Datta, Avijit Dutta, Samir Kundu
In ASIACRYPT'17, Naito proposed a beyond-birthday-bound variant of the LightMAC construction, called LightMAC_Plus, which is built on three independently keyed $n$-bit block ciphers, and showed that the construction achieves $2n/3$-bits PRF security. Later, Kim et al. claimed (without giving any formal proof) its security bound to $2^{3n/4}$. In FSE'18, Datta et al. have proposed a two-keyed variant of the LightMAC_Plus construction, called 2k-LightMAC_Plus, which is built on two independently keyed $n$-bit block ciphers, and showed that the construction achieves $2n/3$-bits PRF security. In this paper, we show a tight security bound on the 2k-LightMAC_Plus construction. In particular, we show that it provably achieves security up to $2^{3n/4}$ queries. We also exhibit a matching attack on the construction with the same query complexity and hence establishing the tightness of the security bound. To the best of our knowledge, this is the first work that provably shows a message length independent $3n/4$-bit tight security bound on a block cipher based variable input length PRF with two block cipher keys.
Long Chen, Hui Guo, Ya-Nan Li, Qiang Tang
Periodic key rotation is a widely used technique to enhance key compromise resilience. Updatable encryption (UE) schemes provide an efficient approach to key rotation, ensuring post-compromise security for both confidentiality and integrity. However, these UE techniques cannot be directly applied to frequently updated databases due to the risk of a malicious server inducing the client to accept an outdated version of a file instead of the latest one.
To address this issue, we propose a scheme called Updatable Secure Storage (USS), which provides a secure and key updatable solution for dynamic databases. USS ensures both data confidentiality and integrity, even in the presence of key compromises. By using efficient key rotation and file update procedures, the communication costs of these operations are independent of the size of the database. This makes USS particularly well-suited for managing large and frequently updated databases with secure version control. Unlike existing UE schemes, the integrity provided by USS holds even when the server learns the current secret key and intentionally violates the key update protocol.
To address this issue, we propose a scheme called Updatable Secure Storage (USS), which provides a secure and key updatable solution for dynamic databases. USS ensures both data confidentiality and integrity, even in the presence of key compromises. By using efficient key rotation and file update procedures, the communication costs of these operations are independent of the size of the database. This makes USS particularly well-suited for managing large and frequently updated databases with secure version control. Unlike existing UE schemes, the integrity provided by USS holds even when the server learns the current secret key and intentionally violates the key update protocol.
Gil Segev, Amit Sharabi, Eylon Yogev
We propose a new notion of knowledge soundness, denoted rogue-instance security, for interactive and non-interactive batch knowledge proofs. Our notion, inspired by the standard notion of rogue-key security for multi-signature schemes, considers a setting in which a malicious prover is provided with an honestly-generated instance $x_1$, and may then be able to maliciously generate related "rogue" instances $x_2,\ldots,x_k$ for convincing a verifier in a batch knowledge proof of corresponding witnesses $w_1,\ldots,w_k$ for all $k$ instances - without actually having knowledge of the witness $w_1$ corresponding to the honestly-generated instance. This setting provides a powerful security guarantee for batch versions of a wide variety of practically-relevant protocols, such as Schnorr's protocol and similar ones.
We present a highly-efficient generic construction of a batch proof-of-knowledge applicable to any algebraic Sigma protocols. The algebraic property refers to a homomorphic structure of the underlying group and includes Schnorr's protocol and others. We provide an almost tight security analysis for our generic batch protocol, which significantly improves upon the previously known security bounds even for the specific case of batch Schnorr protocol. We extend our results beyond algebraic Sigma protocols. We analyze the rogue-instance security of a general batch protocol with plus-one special soundness (a generalization of standard special soundness) and achieve improved security bounds in the generic case.
Our results use a particular type of high-moment assumptions introduced by Rotem and Segev (CRYPTO 2021). These assumptions consider the hardness of a relation against algorithms with bounded expected running time. Although Rotem and Segev introduced these assumptions, they did not provide evidence to support their hardness. To substantiate and validate the high-moment assumptions, we present a new framework for assessing the concrete hardness of cryptographic problems against oracle algorithms with bounded expected runtime. Our framework covers generic models, including the generic group model, random oracle model, and more. Utilizing our framework, we achieve the first hardness result for these high-moment assumptions. In particular, we establish the second-moment hardness of the discrete-logarithm problem against expected-time algorithms in the generic group model.
We present a highly-efficient generic construction of a batch proof-of-knowledge applicable to any algebraic Sigma protocols. The algebraic property refers to a homomorphic structure of the underlying group and includes Schnorr's protocol and others. We provide an almost tight security analysis for our generic batch protocol, which significantly improves upon the previously known security bounds even for the specific case of batch Schnorr protocol. We extend our results beyond algebraic Sigma protocols. We analyze the rogue-instance security of a general batch protocol with plus-one special soundness (a generalization of standard special soundness) and achieve improved security bounds in the generic case.
Our results use a particular type of high-moment assumptions introduced by Rotem and Segev (CRYPTO 2021). These assumptions consider the hardness of a relation against algorithms with bounded expected running time. Although Rotem and Segev introduced these assumptions, they did not provide evidence to support their hardness. To substantiate and validate the high-moment assumptions, we present a new framework for assessing the concrete hardness of cryptographic problems against oracle algorithms with bounded expected runtime. Our framework covers generic models, including the generic group model, random oracle model, and more. Utilizing our framework, we achieve the first hardness result for these high-moment assumptions. In particular, we establish the second-moment hardness of the discrete-logarithm problem against expected-time algorithms in the generic group model.
Yincen Chen, Nana Zhang, Xuanyu Liang, Ling Song, Qianqian Yang, Zhuohui Feng
GIFT is a family of lightweight block ciphers based on SPN structure and composed of two versions named GIFT-64 and GIFT-128. In this paper, we reevaluate the security of GIFT-64 against the rectangle attack under the related-key setting. Investigating the previous rectangle key recovery attack on GIFT-64, we obtain the core idea of improving the attack——trading off the time complexity of each attack phase. We flexibly guess part of the involved subkey bits to balance the time cost of each phase so that the overall time complexity of the attack is reduced. Moreover, the reused subkey bits are identified according to the linear key schedule of GIFT-64 and bring additional advantages for our attacks. Furthermore, we incorporate the above ideas and propose a dedicated MILP model for finding the best rectangle key recovery attack on GIFT-64. As a result, we get the improved rectangle attacks on 26-round GIFT-64, which are the best attacks on it in terms of time complexity so far.
Karim Eldafrawy, Nicholas Genise, Stanislaw Jarecki
Von Ahn, Hopper and Langford introduced the notion of steganographic a.k.a. covert computation, to capture distributed computation where the attackers must not be able to distinguish honest parties from entities emitting random bitstrings. This indistinguishability should hold for the duration of the computation except for what is revealed by the intended outputs of the computed functionality. An important case of covert computation is mutually authenticated key exchange, a.k.a. mutual authentication. Mutual authentication is a fundamental primitive often preceding more complex secure protocols used for distributed computation. However, standard authentication implementations are not covert, which allows a network adversary to target or block parties who engage in authentication. Therefore, mutual authentication is one of the premier use cases of covert computation and has numerous real-world applications, e.g., for enabling authentication over steganographic channels in a network controlled by a discriminatory entity.
We improve on the state of the art in covert authentication by presenting a protocol that retains covertness and security under concurrent composition, has minimal message complexity, and reduces protocol bandwidth by an order of magnitude compared to previous constructions. To model the security of our scheme we develop a UC model which captures standard features of secure mutual authentication but extends them to covertness. We prove our construction secure in this UC model. We also provide a proof-of-concept implementation of our scheme.
We improve on the state of the art in covert authentication by presenting a protocol that retains covertness and security under concurrent composition, has minimal message complexity, and reduces protocol bandwidth by an order of magnitude compared to previous constructions. To model the security of our scheme we develop a UC model which captures standard features of secure mutual authentication but extends them to covertness. We prove our construction secure in this UC model. We also provide a proof-of-concept implementation of our scheme.
Qun Liu, Bart Preneel, Zheng Zhao, Meiqin Wang
Quantum computers hold the potential to solve problems that are intractable for classical computers, thereby driving increased interest in the development of new cryptanalytic ciphers. In NIST's post-quantum standardization process, the security categories are defined by the costs of quantum key search against AES. However, the cost estimates provided by Grassl et al. for the search are high. NIST has acknowledged that these initial classifications should be approached cautiously, since the costs of the most advanced attacks can be significantly reduced. Therefore, accurate resource estimations are crucial for evaluating the security of ciphers against quantum adversaries.
This paper presents a set of generic techniques for implementing AES quantum oracles, which are essential for quantum attacks such as Grover's algorithms. Firstly, we introduce the mixing-XOR technique to reuse the ancilla qubits. At ASIACRYPT 2022, Huang et al. proposed an S-box structure with 120 ancilla qubits. We are able to reduce the number of ancilla qubits to 83 without increasing the T-depth. Secondly, we propose the combined pipeline architecture with the share technique to combine the S-box and its reverse, which achieves it with only 98 ancilla qubits, resulting in a significant reduction of 59% compared to the independent structure. Thirdly, we use a general algorithm to determine the depth of quantum circuits, searching for the in-place circuit of AES MixColumns with depth 16. Applying these improvements, we achieve the lower quantum depth of AES circuits, obtaining more precise resource estimates for Grover's algorithm. For AES-128, -192, and -256, we only require the depth of 730, 876, and 1,018, respectively.
Recently, the community has also focused on the trade-off of the time and space cost of quantum circuits for AES. In this regard, we present quantum implementations of AES circuits with a lower DW-cost on the zig-zag architecture. Compared with the circuit proposed by Huang et al., the DW-cost is reduced by 35%.
Helger Lipmaa
Gentry and Wichs proved that adaptively sound SNARGs for hard languages need non-falsifiable assumptions. Lipmaa and Pavlyk claimed Gentry-Wichs is tight by constructing a non-adaptively sound zk-SNARG FANA for NP from falsifiable assumptions. We show that FANA is flawed. We define and construct a fully algebraic $F$-position-binding vector commitment scheme VCF. We construct a concretely efficient commit-and-prove zk-SNARK Punic, a version of FANA with an additional VCF commitment to the witness. Punic satisfies semi-adaptive black-box $G$-knowledge-soundness, a new natural knowledge-soundness notion for commit-and-prove SNARKs. We use a new proof technique to achieve global consistency using a functional somewhere-extractable commitment scheme to extract vector commitment's local proofs.
Jonathan Bootle, Sebastian Faller, Julia Hesse, Kristina Hostáková, Johannes Ottenhues
Fuzzy Password-Authenticated Key Exchange (fuzzy PAKE) allows cryptographic keys to be generated from authentication data that is both fuzzy and of low entropy. The strong protection against offline attacks offered by fuzzy PAKE opens an interesting avenue towards secure biometric authentication, typo-tolerant password authentication, and automated IoT device pairing. Previous constructions of fuzzy PAKE are either based on Error Correcting Codes (ECC) or generic multi-party computation techniques such as Garbled Circuits. While ECC-based constructions are significantly more efficient, they rely on multiple special properties of error correcting codes such as maximum distance separability and smoothness.
We contribute to the line of research on fuzzy PAKE in two ways. First, we identify a subtle but devastating gap in the security analysis of the currently most efficient fuzzy PAKE construction (Dupont et al., Eurocrypt 2018), allowing a man-in-the-middle attacker to test individual password characters. Second, we provide a new fuzzy PAKE scheme based on ECC and PAKE that provides a built-in protection against individual password character guesses and requires fewer, more standard properties of the underlying ECC. Additionally, our construction offers better error correction capabilities than previous ECC-based fuzzy PAKEs.
Yi Chen, Zhenzhen Bao, Hongbo Yu
The differential-linear attack is one of the most effective attacks against ARX ciphers. However, two technical problems are preventing it from being more effective and having more applications: (1) there is no efficient method to search for good differential-linear approximations. Existing methods either have many constraints or are currently inefficient. (2) partitioning technique has great potential to reduce the time complexity of the key-recovery attack, but there is no general tool to construct partitions for ARX ciphers. In this work, we step forward in solving the two problems. First, we propose a novel idea for generating new good differential-linear approximations from known ones, based on which new searching algorithms are designed. Second, we propose a general tool named partition tree, for constructing partitions for ARX ciphers. Based on these new techniques, we present better attacks for two ISO/IEC standards, i.e., LEA and Speck. For LEA, we present the first 17-round distinguisher which is 1 round longer than the previous best distinguisher. Furthermore, we present the first key recovery attacks on 17-round LEA-128, 18-round LEA-192, and 18-round LEA-256, which attack 3, 4, and 3 rounds more than the previous best attacks. For Speck, we find better differential-linear distinguishers for Speck48 and Speck64. The first differential-linear distinguishers for Speck96 and Speck128 are also presented.
Xiang Liu, Ying Gao
Multi-party private set union (MPSU) allows \(k(k\geq 3)\) parties, each holding a dataset of known size, to compute the union of their sets without revealing any additional information. Although two-party PSU has made rapid progress in recent years, applying its effective techniques to the multi-party setting would render information leakage and thus cannot be directly extended. Existing MPSU protocols heavily rely on computationally expensive public-key operations or generic secure multi-party computation techniques, which are not scalable.
In this work, we present a new efficient framework of MPSU from multi-party secret-shared shuffle and a newly introduced protocol called multi-query secret-shared private membership test (mq-ssPMT). Our MPSU is mainly based on symmetric-key operations and is secure against any semi-honest adversary that does not corrupt the leader and clients simultaneously. We also propose new frameworks for computing other multi-party private set operations (MPSO), such as the intersection, and the cardinality of the union and the intersection, meeting the same security requirements.
We demonstrate the scalability of our MPSU protocol with an implementation and a comparison with the state-of-the-art MPSU. Experiments show that when computing on datasets of \(2^{10}\) elements, our protocol is \(109\times\) faster than the state-of-the-art MPSU, and the improvement becomes more significant as the set size increases. To the best of our knowledge, ours is the first protocol that reports on large-size experiments. For 7 parties with datasets of \(2^{20}\) elements each, our protocol requires only 46 seconds.
In this work, we present a new efficient framework of MPSU from multi-party secret-shared shuffle and a newly introduced protocol called multi-query secret-shared private membership test (mq-ssPMT). Our MPSU is mainly based on symmetric-key operations and is secure against any semi-honest adversary that does not corrupt the leader and clients simultaneously. We also propose new frameworks for computing other multi-party private set operations (MPSO), such as the intersection, and the cardinality of the union and the intersection, meeting the same security requirements.
We demonstrate the scalability of our MPSU protocol with an implementation and a comparison with the state-of-the-art MPSU. Experiments show that when computing on datasets of \(2^{10}\) elements, our protocol is \(109\times\) faster than the state-of-the-art MPSU, and the improvement becomes more significant as the set size increases. To the best of our knowledge, ours is the first protocol that reports on large-size experiments. For 7 parties with datasets of \(2^{20}\) elements each, our protocol requires only 46 seconds.
Zhuang Shan, Leyou Zhang, Qing Wu, Qiqi Lai
The main focus of this article is on an open problem, namely the Ring-SIS reduction problem.We first utilize a spatial isomorphism approach to reduce the Ring-SIS problem to the classic SIS problem in lattices, indirectly reducing it to the classic SIVP in lattices. This provides theoretical assurance to some extent for the difficulty and resistance against quantum attacks of the Ring-SIS
problem.
Additionally, we reduce the Ring-LWE problem to the Ring-SIS problem, which guarantees the security of encryption schemes based on Ring-LWE to a certain degree. Finally, this article proves that the difficulty of the Ring-SIS problem and the Ring-LWE problem is relatively average with respect to the spatial dimension or polynomial degree.
Additionally, we reduce the Ring-LWE problem to the Ring-SIS problem, which guarantees the security of encryption schemes based on Ring-LWE to a certain degree. Finally, this article proves that the difficulty of the Ring-SIS problem and the Ring-LWE problem is relatively average with respect to the spatial dimension or polynomial degree.