<div> Mixnet protocols are used in electronic voting protocols to mix the ballot box before the tally, to preserve ballots privacy and unlinkabiliy. Whereas proving security properties of the other components of the electronic voting protocols has globally already been done in several logical frameworks and tools, proofs of mixnets remain a real challenge to handle. In this paper we focus on the quite recent CCSA logic, which enables handling of computational security proofs with first-order logics facilities. We enrich the logic to be able to deal with zero-knowledge proofs and rewinding techniques, and provide the first complete proof of Terelius-Wikström mixnet protocol. </div>
Nojan Sheybani, Anees Ahmed, Michel A. Kinsy, Farinaz Koushanfar
Zero-Knowledge Proofs (ZKPs) are a cryptographic primitive that allows a prover to demonstrate knowledge of a secret value to a verifier without revealing anything about the secret itself. ZKPs have shown to be an extremely powerful tool, as evidenced in both industry and academic settings. In recent years, the utilization of user data in practical applications has necessitated the rapid development of privacy-preserving techniques, including ZKPs. This has led to the creation of several robust open-source ZKP frameworks. However, there remains a significant gap in understanding the capabilities and real-world applications of these frameworks. Furthermore, identifying the most suitable frameworks for the developers' specific applications and settings is a challenge, given the variety of options available. The primary goal of our work is to lower the barrier to entry for understanding and building applications with open-source ZKP frameworks. In this work, we survey and evaluate 25 general-purpose, prominent ZKP frameworks. Recognizing that ZKPs have various constructions and underlying arithmetic schemes, our survey aims to provide a comprehensive overview of the ZKP landscape. These systems are assessed based on their usability and performance in SHA-256 and matrix multiplication experiments. Acknowledging that setting up a functional development environment can be challenging for these frameworks, we offer a fully open-source collection of Docker containers. These containers include a working development environment and are accompanied by documented code from our experiments. We conclude our work with a thorough analysis of the practical applications of ZKPs, recommendations for ZKP settings in different application scenarios, and a discussion on the future development of ZKP frameworks.
Chhavi Yadav, Evan Monroe Laufer, Dan Boneh, Kamalika Chaudhuri
In principle, explanations are intended as a way to increase trust in machine learning models and are often obligated by regulations. However, many circumstances where these are demanded are adversarial in nature, meaning the involved parties have misaligned interests and are incentivized to manipulate explanations for their purpose. As a result, explainability methods fail to be operational in such settings despite the demand \cite{bordt2022post}. In this paper, we take a step towards operationalizing explanations in adversarial scenarios with Zero-Knowledge Proofs (ZKPs), a cryptographic primitive. Specifically we explore ZKP-amenable versions of the popular explainability algorithm LIME and evaluate their performance on Neural Networks and Random Forests. Our code is publicly available at https://github.com/emlaufer/ExpProof.
Zero-knowledge proofs validate statements without revealing any information, pivotal for applications such as verifiable outsourcing and digital currencies. However, their broad adoption is limited by the prolonged proof generation times, mainly due to two operations: Multi-Scalar Multiplication (MSM) and Number Theoretic Transform (NTT). While MSM has been efficiently accelerated using multi-GPU systems, NTT has not, due to the high inter-GPU communication overhead incurred by its permutation data access pattern.
Tao Lu, Yuxun Chen, Zonghui Wang, Xiaohang Wang · 6 authors
Zero-knowledge proof (ZKP) is a cryptographic primitive that enables one party to prove the validity of a statement to other parties without disclosing any secret information. With its widespread adoption in applications such as blockchain and verifiable machine learning, the demand for generating zero-knowledge proofs has increased dramatically. In recent years, considerable efforts have been directed toward developing GPU-accelerated systems for proof generation. However, these previous systems only explored efficiently generating a single proof by reducing latency rather than batch generation to provide high throughput.
Zero-knowledge proof (ZKP) is an important cryptographic tool that sees wide applications in real-world scenarios where privacy must be protected, including privacy-preserving blockchains and zero-knowledge machine learning. Existing ZKP acceleration approaches using GPUs, FPGAs, and ASICs focus only on classic protocols that rely on expensive elliptic curve arithmetics. Emerging ZKP protocols based on hash functions can greatly reduce the algorithmic complexity, but they also introduce much more diverse computation kernels that cannot be efficiently handled by a single accelerator chip if dedicated units for each kernel are used. Our approach is to leverage a unified hardware architecture that is able to efficiently support the common primitives in ZKP, and then use smart mapping strategies to flexibly map various kernels to such hardware while ensuring high resource utilization. We design UniZK as such a ZKP accelerator, with a systolic-array-based hardware architecture enhanced with extra local links and a new vector processing mode. We propose novel mapping strategies to support diverse kernels including number theoretic transforms, hash functions, and general polynomial computations. UniZK provides 97x and 46x speedups on average compared to the CPU and GPU implementations of the same protocols, and is also 840x faster than previous ZKP accelerators using different protocols.
Faisal Yusuf, Riya Widayanti, Sausan Raihana Putri, Aulia Wellington
Blockchain technology has gained widespread adoption across various industries due to its decentralized and transparent nature. However, its inherent characteristics, such as immutability and openness, expose the system to critical security threats and privacy concerns. This study aims to develop a comprehensive framework to enhance blockchain security and privacy, addressing prevalent challenges such as data breaches, transaction anonymity, and resistance to cyberattacks. The proposed framework integrates advanced cryptographic techniques, including Zero Knowledge Proofs (ZKP), Secure Multi Party Computation (SMPC), and enhanced encryption protocols, alongside innovative consensus mechanisms to improve system robustness. A simulation-based evaluation and a real-world case study were conducted to validate the framework. The results demonstrate significant improvements in mitigating security vulnerabilities, such as 51% attacks and double spending, while ensuring enhanced privacy through anonymized data handling and confidentiality-preserving transactions. Furthermore, the case study confirmed the framework's practicality and adaptability across diverse applications. These findings highlight the proposed framework's potential to establish a secure and privacy-preserving blockchain ecosystem, offering a solid foundation for future research and implementation in both public and private blockchain networks.
It is becoming harder to manage the growing amounts of waste generated daily at an increasing rate. These problems require an efficient solution that guarantees effectiveness and transparency and maintains trust within the community. To improve the process of traditional waste management, we proposed a unique solution, “GREENLINK”, which uses a combination of blockchain technology with the concept of zero-knowledge proofs (ZKPs), non-fungible tokens (NFTs), and Walrasian equilibrium. Zero-knowledge proofs (cryptographic protocols) are used to verify organizations and prove compliance (e.g., certification, recycling capacity) without disclosing sensitive information. Through an iterative bidding process, the proposed framework employs Walrasian equilibrium, a technique to balance supply and demand, guaranteeing equitable pricing and effective resource distribution among participants. The transactions and waste management activities are securely recorded on an immutable ledger, ensuring accountability, traceability, and transparency. The performance of the proposed model is evaluated. Parameters like average latency, TPS, and memory consumption are calculated using Hyperledger Caliper (a blockchain performance benchmark framework).
This paper introduces RoSeMary, the first-of-its-kind ML/Crypto codesign watermarking framework that regulates LLM-generated code to avoid intellectual property rights violations and inappropriate misuse in software development. High-quality watermarks adhering to the detectability-fidelity-robustness tri-objective are limited due to codes' low-entropy nature. Watermark verification, however, often needs to reveal the signature and requires re-encoding new ones for code reuse, which potentially compromising the system's usability. To overcome these challenges, RoSeMary obtains high-quality watermarks by training the watermark insertion and extraction modules end-to-end to ensure (i) unaltered watermarked code functionality and (ii) enhanced detectability and robustness leveraging pre-trained CodeT5 as the insertion backbone to enlarge the code syntactic and variable rename transformation search space. In the deployment, RoSeMary uses zero-knowledge proofs for secure verification without revealing the underlying signatures. Extensive evaluations demonstrated RoSeMary achieves high detection accuracy while preserving the code functionality. RoSeMary is also robust against attacks and provides efficient secure watermark verification.
Ichsan Nur Ahmad, Parman Sukarno, Aulia Arif Wardana
This research paper presents the development of an electronic voting system that utilizes blockchain technology and Zero Knowledge Proof to enhance privacy and security during voting. Electronic voting systems have many issues regarding privacy, data integrity, and proper transparency, whereas traditional voting systems face the issue of being cost-effective. This research has solved the previously mentioned issues by using ZKP over the polygon network. Furthermore, ZKP, along with blockchain technology, helps in the decen-tralization, immutability, and transparency of the stored data while maintaining the confidentiality of the voter identity in the process of authentication and vote validation. Moreover, cryptographic verification is aided through role management and a user interface, which results in a quicker verification process than traditional methods. Using a polygon network as the medium for conducting tests has shown a low transaction cost of 0.010 POL to facilitate voting while providing substantial privacy. The approach presented in this research has significantly improved over traditional E-voting systems in terms of cost, security, and scalability, indicating that this approach is better suited for election processes today.
The work examines modern approaches to building electronic voting systems, such as blockchain, which promises to revolutionize the process due to its immutability and decen-tralization properties, as well as traditional cryptographic methods, including homomorphic encryption, which allows vote counting without the need to decrypt each individual vote. Blind signatures ensure the ability to confirm a vote without disclosing the user's identity, and zero-knowledge proofs allow voting without interacting with the server. The goal of the work is to select an approach for building electronic voting systems based on a comparative analy-sis of their key characteristics. The solved tasks include reviewing the requirements, general-ized structures, and main procedures of electronic voting systems; analyzing the existing types of electronic voting systems and their comparative characteristics. During the work, existing systems and other literature were thoroughly analyzed. The article provides a de-tailed analysis of the advantages and limitations of these technologies, as well as their suit-ability for different electoral systems, considering important aspects such as scalability, effi-ciency, and protection against potential threats. Throughout the work, a list of requirements for electronic voting systems was compiled, the main procedures present in electronic voting systems were outlined, a set of actors in typical electronic voting systems was defined, and the generalized structures of their main types were presented. A comparative analysis of the types of electronic voting systems based on compliance with the requirements was conducted. An approach was chosen for further system development.
Zero Knowledge (ZK) proofs are protocols with growing applications in fields such as cryptography. They can be particularly difficult to design and thus have multiple domain-specific languages (DSLs) to aid a programmer in their construction. Analysis methods for these protocols are then typically language-specific, greatly limiting their utility. Most languages compile user code into a midpoint polynomial-circuit called a rank one constraint system (R1CS). We provide tools to analyse these R1CS circuits which hence have much broader applicability than existing tools. Specifically, we design and implement a tool for equivalence up to renaming and scaling, useful to avoid repeating a laborious step of the ZK process. As implemented, the tool can handle circuits on the order of millions of constraints. Additionally, we provide methods to extract a directed acyclic hierarchical structure via clustering to guide an automated property prover with recursive proving. Such a structure typically exists in DSL code but is lost when compiled to R1CS and is required to make larger circuits feasible to pass to a property prover. The guidance given by our clustering methods to the property prover Civer gave comparable results to the guidance of the original structure present in the code and finished in faster time.
Yong Yu, Qian Zhang, Yannan Li, Y. Yao · 5 authors
Auctions conducted via wireless devices have promoted trade worth trillions of dollars globally. Their potential market share and crucial role in resource allocation make them an appealing research topic. However, sealed-bid auctions are usually considered high-risk behaviors for bidders due to their unequal status, dependence on auctioneers, and lack of transparency during an auction. In order to meet these requirements for confidentiality, integrity, and availability of data and reduce communication complexity between wireless devices, in this article, we propose a trustworthy sealed-bid auction protocol in wireless networks with low communication costs. Specifically, the protocol adopts cryptographic techniques such as commitment and zero-knowledge proofs to ensure the validity of bids and the credibility of auction results. Inner-product arguments of vectors and proof of aggregation are employed to reduce communication costs of the proposal. The protocol guarantees the continuous verification of submitted data throughout the process (before, during, and at the end) of an auction so as to grant admission to network resources. We show that the proposed protocol satisfies privacy protection, public verifiability, fairness, and non-repudiation of bidders and auctioneers. In addition, our construction is generic, and the protocol can be extended to ordinal-price sealed-bid auctions. The time consumption evaluated in the implementation indicates the feasibility of the protocol in real-world applications.
Zero-knowledge proofs (ZKPs) are widely applied in digital economies, such as cryptocurrencies and smart contracts, for establishing trust and privacy between untrusted parties. Classical ZKPs rely on computational assumptions and are vulnerable to quantum attacks. While a recent advance suggests quantum-sound symmetric relativistic ZKPs for the graph three-coloring problem without computational assumptions, the high round complexity, which leads to unachievable runtime and overall randomness cost, renders them impractical for real-life deployment. To overcome this, we develop an efficient asymmetric relativistic ZKP protocol using relativistic bit commitments, and prove its quantum soundness by relating it to the nonlocal Clauser-Horne-Shimony-Holt (CHSH) game. Our protocol achieves a linear relationship between the round complexity and the number of edges, and thus significantly improves practical feasibility. In addition, we implement a proof-of-principle experiment which completes all interactive rounds in about 0.22 seconds and requires an overall randomness cost of 430.81 MB. Our work illustrates the powerful potential of integrating special relativity with quantum theory in trustless cryptography, paving the way for robust applications against quantum attacks in distrustful Internet environments. Zero-knowledge proofs can protect privacy online, but almost all current methods are vulnerable to quantum attacks. Here, the authors report an efficient relativistic protocol and experiment that resists quantum attacks and greatly reduces runtime, randomness cost and communication rounds.
The proliferation of Internet of Things (IoT) devices in smart environments has created unprecedented challenges in identity management and security. Traditional centralized identity management systems face scalability, privacy, and single-point-of-failure issues when applied to IoT ecosystems. This paper presents a novel blockchain-based framework for decentralized identity management in smart IoT environments. Our proposed framework leverages blockchain technology's immutable ledger, smart contracts, and cryptographic mechanisms to provide secure, scalable, and privacy-preserving identity management for IoT devices. The framework incorporates a multi-layered security architecture that includes device authentication, access control, and identity verification mechanisms. Experimental results demonstrate that our approach achieves 99.7% authentication accuracy with reduced latency compared to traditional centralized systems. The framework also provides enhanced privacy protection through zero-knowledge proofs and selective disclosure mechanisms. This research contributes to the advancement of secure IoT identity management and provides a foundation for future developments in decentralized IoT security
Qi An, Frank Jiang, Chengzu Dong, Shantanu Pal · 7 authors
The rapid expansion of electric vehicle (EV) infrastructure necessitates advanced solutions for secure and private authentication at EV charging stations. This research introduces a blockchain-based framework enhanced with self-sovereign identity (SSI) features, targeting the improvement of privacy and security in cyber marketplaces for EVs. The inclusion of SSI enables users to maintain full control over their digital identities, a critical advancement for authentication processes at EV charging stations. This system effectively addresses the growing privacy and security challenges within the expanding EV infrastructure. By integrating Zero-knowledge proof with self-sovereign identity, the framework not only ensures robust security but also preserves user privacy by enabling users to prove their identity without exposing sensitive personal information. We propose an efficient and user-friendly solution, showcasing its potential as a pioneering innovation in the field of EV charging infrastructure.
Collision-resistant cryptographic hash functions (CRHs) are crucial for security, particularly for message authentication in Zero-knowledge Proof (ZKP) applications. However, traditional CRHs like SHA-2 or SHA-3, while optimized for CPUs, generate large circuits, rendering them inefficient in the ZK domain. Conversely, ZK-friendly hashes are designed for circuit efficiency but struggle on conventional hardware, often orders of magnitude slower than standard hashes due to their reliance on expensive finite field arithmetic. To bridge this performance gap, we present HashEmAll, a novel collection of FPGA-based realizations for three prominent ZK-friendly hashes: Griffin, Rescue-Prime, and Reinforced Concrete. Each offers distinct optimization profiles, with both area-optimized and latency-optimized variants available, allowing users to tailor hardware selection to specific application constraints regarding resource utilization and performance. Our extensive evaluation shows that latency-optimized HashEmAll designs outperform CPU implementations by at least $10 \times$, with the leading design achieving a $23 \times$ speedup. These gains are coupled with lower power consumption and compatibility with accessible FPGAs. Importantly, the highly parallel and pipelined architecture of HashEmAll enables significantly better practical scaling than CPU-based approaches towards building real-world ZKP applications, such as data commitments with Merkle Trees, by mitigating the hashing bottleneck for large trees. This highlights the suitability of HashEmAll for real-world ZKP applications involving large-scale data authentication. We also highlight the ability to translate the HashEmAll methodology to various ZK-friendly hash functions and different field sizes.
As more users seek generative AI (GAI) models to enhance work efficiency, GAI and Model-as-a-Service will drive transformative changes and upgrades across all industries. However, when users utilize GAI models provided by the service provider, they cannot be certain that the model’s quality matches the provider’s claims. Considering the need to protect intellectual property, the service provider will not disclose model details for user verification. To this end, we take the Internet of Vehicles as research background, proposing a zero knowledge model proof architecture based on UAVs. We also introduce a multiagent reinforcement learning algorithm to optimize the verification process. In specific, we first propose a verification scheme for the key operations of generative adversarial networks based on noninteractive zero knowledge proof. The zero knowledge proof architecture ensures that model parameters cannot be stolen during the verification process. After that, we propose an Age of Verification (AoV) metric to ensure the timeliness and freshness of zero knowledge proof. We also construct a tradeoff optimization problem between the energy consumption of UAV as a verifier and the AoV of edge servers as service providers, and transform the problem based on Lyapunov optimization theory. Following that, we propose an enhanced multiagent proximal policy optimization algorithm to enable the collaborative verification of edge servers by multiple UAVs. The algorithm simulation results demonstrate that the reward value of our proposed algorithm is over 10% higher than that of the standard algorithm, with a faster and more stable overall convergence speed. Additionally, the zero knowledge proof performance test results indicate that the verification delay in our proposed architecture is less than 500 ms during the verification phase, meeting practical requirements.
This paper comprehensively discusses the security mechanism of blockchain-based digital currency transactions, from the application of distributed ledgers, consensus algorithms, smart contracts, to the implementation of multiple signatures and cold storage schemes, to advanced privacy protection technologies, such as zero-knowledge proofs and homomorphic encryption. In particular, we delve into innovative mechanisms for attack prevention, including the fusion of heterogeneous multi-chain architectures with PoW+PoS hybrid consensus models. The article also details the practice of performance evaluation and security testing through a series of carefully designed experiments such as throughput and latency testing under different loads, resource utilization monitoring, and security reviews and comparisons with competitors. Experimental results show that the system exhibits good throughput growth under high load, but with the increase of latency, resource utilization is efficient and tends to saturation, most of the security protection mechanisms meet the standards, but access control problems that need to be optimized and high-risk vulnerabilities to be repaired are also found.
Satellite communication (SC) is an indispensable component of future communication systems due to its extensive coverage and flexibility. In this work, we investigate the fine-grained anonymous access technique, which not only ensures user equipments (UEs) privacy in the open SC environment but also enables satellites to enforce fine-grained access policies with low overhead. Firstly, we design a Merkle forest based framework that facilitates efficient UE attribute data synchronization, leveraging the broadcasting capability of satellites. Subsequently, we construct a zero-knowledge based protocol for UE authentication, key agreement, and handover in SC. The analysis demonstrates the protocol's resilience against prevalent attacks, and simulation results validate its practicality.
As a global virtual environment, the metaverse poses various challenges regarding data storage, sharing, interoperability, and privacy preservation. Typically, a trusted third party (TTP) is considered necessary in these scenarios. However, relying on a single TTP may introduce biases, compromise privacy, or lead to single-point-of-failure problem. To address these challenges and enable secure data exchange in the metaverse, we propose a system based on decentralized TTPs and the Ethereum blockchain. First, we use the threshold ElGamal cryptosystem to create the decentralized TTPs, employing verifiable secret sharing (VSS) to force owners to share data honestly. Second, we leverage the Ethereum blockchain to serve as the public communication channel, automatic verification machine, and smart contract engine. Third, we apply discrete logarithm equality (DLEQ) algorithms to generate non-interactive zero knowledge (NIZK) proofs when encrypted data is uploaded to the blockchain. Fourth, we present an incentive mechanism to benefit data owners and TTPs from data-sharing activities, as well as a penalty policy if malicious behavior is detected. Consequently, we construct a data exchange framework for the metaverse, in which all involved entities are accountable. Finally, we perform comprehensive experiments to demonstrate the feasibility and analyze the properties of the proposed system.
Abstract Blockchain-based data transaction protocols augmented with zero-knowledge proofs offer fairness to the participants, yet they encounter challenges pertaining to both security and efficiency. We propose the zk-DSTARK, a zk-STARK-based protocol that enables distributed generation of zero-knowledge proofs, significantly reducing the computational burden. And zk-DSTARK inherits zk-STARK’s feature of single proof generation for multiple uses, improving the efficiency of successive transactions. Furthermore, we propose a fair exchange system named zk-DCIAExchange for off-chain verification, which is based on zk-DSTARK and intel software guard extensions (SGX). This system not only minimizes on-chain overhead but also ensures the security and fairness of the transaction. Experimental results show that, in continuous transactions scenarios, the time overhead for subsequent transactions is diminished by 99.9% compared to the first transaction; compared to zero knowledge contingent payment (ZKCSP), our scheme achieves a remarkable 92% reduction in time overhead, and a 26.3% reduction when compared to FairSwap; with 32 distributed nodes and a trace length of 216, the proof generation time is reduced by ~85.45%; the additional verification time introduced by the SGX is ~0.45 s, which is deemed acceptable, and the on-chain verification overhead is reduced by ~7.2% compared to the ZKCSP and ~54.4% compared to FairSwap.