Blockchain Papers

Carsten Baum, James Hsin-yu Chiang, Bernardo David, Tore Kasper Frederiksen

No abstract is available for this record.

Sharon Rose H, Razeenath Aafiya A, Kamachi Swetha R, G. R. Ramya

The system focuses on proposing a robust authentication framework based on these Secure Remote Password (SRP) protocol to enhance the security of data exchange in Peer-to- Peer (P2P) cloud environments. The Advanced Encryption Standard (AES) algorithm provides encryption and the SRP protocol leverages cryptographic primitives to establish mutual authentication between cloud servers and users, ensures that data, remains protected against any vulnerabilities. The system encompasses various stages, including user registration, key establishment, and secure data transmission. After user registration, the SRP protocol employs a zero-knowledge proof mechanism to maintain the security of data available on cloud servers, mitigating the risks associated with password leaks and unauthorized access. Furthermore, the protocol facilitates secure key exchange to establish a confidential communication channel between peers, enabling encrypted data transmission. The system integrates SRP protocol and AES encryption, fortifying data security in P2P cloud environments through robust authentication, ensuring a comprehensive defence against potential vulnerabilities.

Zhiheng Qiu, Wentao Li, Qianhang Huang, Yutong Sun · 7 authors

With the widespread adoption of blockchain technology across diverse sectors[1], the imperative for efficient data storage and retrieval mechanisms has intensified[2]. This paper introduces an innovative approach that synergizes Zero-Knowledge Proofs (ZKP) and sharding techniques to bolster data privacy and optimize storage within blockchain systems. We present an exhaustive analysis of prevailing blockchain data storage mechanisms, pinpoint their inherent privacy vulnerabilities, and elucidate the potential of ZKP in mitigating these concerns. Furthermore, we propose a sharding-centric solution that not only fortifies data privacy but also augments the efficiency of data retrieval[3]. Experimental results, derived from real-world scenarios, validate the robustness and efficiency of our proposed methodology.

Manqi Yue

The rise of technology has brought with it a heightened awareness of the necessity to shield personal data and maintain exclusive access to specific knowledge. A notable solution that emerged from this consciousness is Zero-Knowledge Proofs (ZKPs) and, more specifically, Schnorr’s Protocol. Historically, Zero-Knowledge Proofs have a compelling lineage, tracing their roots back to the fervent discussions among cryptographers aiming to achieve a balance between information sharing and privacy. ZKPs are cryptographic methods that allow one party to prove to another that a statement is true, without revealing any specific information about the statement itself. In the midst of these developments, Schnorr’s Protocol emerged as a renowned interactive proof system. It possesses an intuitive structure that has made it pivotal in the enhancement of digital security. The typical flow of Schnorr’s Protocol begins with the prover sending a commitment to the verifier. The verifier then sends a random challenge back to the prover, who, in turn, produces a response. What’s captivating is that the verifier can ascertain the validity of the proof without gaining insight into the underlying secret. Interactive Schnorr’s Protocol involves real-time back-and-forth communication between the prover and verifier. On the other hand, the non-interactive version eliminates this need by using a cryptographic hash function, thereby streamlining the process.

Bin Lian, Jialin Cui, Hongyuan Chen, Xianghong Zhao · 7 authors

Many IoT applications require users to share their devices’ location, and enhanced privacy-protection means sharing location anonymously, unlinkably and without relying on any administrators. But under such protection, it is difficult to trust shared location data, which may be from unregistered devices or from the same one’s multiple logins or from the cloned device ID, even be generated by an attacker without any devices! Such untrusted location sharing cheats system, misleads users, even attacks system. To the best of our knowledge, such problems have not been solved in a decentralized system. To solve them in one scheme, we put forward the first decentralized accumulator for device registration and construct the first practical decentralized anonymous authentication for device login. When logging in, the device provides a special knowledge proof, which integrates zero-knowledge (for privacy) with knowledge-leakage (for identifying abnormal behaviors) designing for blockchain (for decentralization). Therefore, in our system, only registered IoT devices can upload location data and their logins are anonymous and unlinkable, while login exceeding${K}$times in a system period or cloning ID to login concurrently can be identified and tracked without any trusted centers. In addition, we provide the security proofs and the application examples of the proposed scheme. And the efficiency analysis and experimental data show that the performance of our scheme can meet the needs of real-world location sharing on IoT.

Takuma Yoshioka, Toru Nakanishi, Teruaki Kitasuka

A system of zero-knowledge proofs on graph signatures has been proposed, where a graph can be signed, and the owner of the graph signature can prove a graph relation such as the connectivity and isolation of any two vertexes on the graph without disclosing all information about the graph. The correctness of the graph information is guaranteed by the signature. One of the applications is a virtualized infrastructure, where an infrastructure provider manages a distributed system, and each tenant is allocated a specific portion of this infrastructure for use. Tenants need to check with the provider that their resources are properly connected (connectivity) and that their resources are properly separated from the resources of other tenants (isolation). On the other hand, the provider cannot simply disclose the entire infrastructure topology to each tenant. Using the zero-knowledge proof system on graph signatures, both requirements can be addressed. Previously, an efficient zero-knowledge proof system on graph signatures using a bilinear-map accumulator has been proposed, where the verification time and the size of the proof data do not depend on the number of graph vertexes and edges. However, this system has two problems. First, since the proof does not include labels, it is not possible to prove the connectivity considering network bandwidth and cost. Second, since it assumes undirected graphs, it cannot handle applications on directed graphs such as network flows. In this paper, we extend the previous system and propose a zero-knowledge proof system of the connectivity for directed graphs where each edge has labels. We implemented our system on a PC using a pairing library and evaluate it by measuring the processing times. Compared to the conference version of this paper, we show the formal definitions and the security proofs of our proposed system, and add implementation-based evaluations reflecting the application to the virtualized infrastructure.

Zongyang Zhang, Weihan Li, Ximeng Liu, Xin Chen · 5 authors

Zero-knowledge scalable transparent arguments of knowledge (zk-STARKs) are a promising approach to solving the blockchain scalability problem while maintaining security, decentralization and privacy. However, compared with zero-knowledge proofs with trusted setups deployed in existing scalability solutions, zk-STARKs are usually less efficient. In this paper, we introduce Ligerolight, an optimized zk-STARK for the arithmetic circuit satisfiability problem following the framework of Ligero (ACM CCS 2017) and Aurora (Eurocrypt 2019) based on interactive oracle proof, which could be used for blockchain scalability. Evaluations show that Ligerolight has performance advantages compared with existing zk-STARKs. The prover time is 30% faster than Aurora to generate proof for computing an authentication path of a Merkle tree with 32 leaves. The proof size is about 131KB, one-tenth of Ligero and 50% smaller than Aurora. The verifier time is 2 times as fast as Aurora. Underlying Ligerolight is a new batch zero-knowledge inner product argument, allowing to prove multiple inner product relations once. Using this argument, we build a batch multivariate polynomial commitment with poly-logarithmic communication complexity and verification. This polynomial commitment is particularly efficient when opening multiple points in multiple polynomials at one time, and may be of independent interest in constructing scalability solutions.

Anastasia E. Skorobogatova, Natalia G. Butakova

Existing distributed ledger systems ensure the integrity and availability of information, but they lack built-in mechanisms to ensure the confidentiality of transaction data recorded in the ledger. Any intruder can obtain all transaction data by downloading a copy of the ledger and trace the relationships between transactions and accounts. Thus, additional mechanisms are needed to ensure the confidentiality of transactions. One solution to this problem is to use a zero-knowledge proof protocol. This article discusses the use of zero-knowledge proof to ensure the confidentiality of transactions in distributed ledger systems. We consider both the UTXO-model and the account model.

Yizheng Zhu, Yuncheng Wu, Zhaojing Luo, Beng Chin Ooi · 5 authors

Federated Learning (FL) emerges as a viable solution to facilitate data collaboration, enabling multiple clients to collaboratively train a machine learning (ML) model under the supervision of a central server while ensuring the confidentiality of their raw data. However, existing studies have unveiled two main risks: (i) the potential for the server to infer sensitive information from the client's uploaded updates (i.e., model gradients), compromising client input privacy, and (ii) the risk of malicious clients uploading malformed updates to poison the FL model, compromising input integrity. Recent works utilize secure aggregation with zero-knowledge proofs (ZKP) to guarantee input privacy and integrity in FL. Nevertheless, they suffer from extremely low efficiency and, thus, are impractical for real deployment. In this paper, we propose a novel and highly efficient approach RiseFL for secure and verifiable data collaboration, ensuring input privacy and integrity simultaneously. Firstly, we devise a probabilistic integrity check method that transforms strict checks into a hypothesis test problem, offering great optimization opportunities. Secondly, we introduce a hybrid commitment scheme to satisfy Byzantine robustness with improved performance. Thirdly, we present an optimized ZKP generation and verification technique that significantly reduces the ZKP cost based on probabilistic integrity checks. Furthermore, we theoretically prove the security guarantee of RiseFL and provide a cost analysis compared to state-of-the-art baselines. Extensive experiments on synthetic and real-world datasets suggest that our approach is effective and highly efficient in both client computation and communication. For instance, RiseFL is up to 28x, 53x, and 164x faster than baselines ACORN, RoFL, and EIFFeL for the client computation.

Firas Hamila, Mohammad Hamad, Daniel Costa Salgado, Sebastian Steinhorst

Abstract With the rapid expansion of IoT devices and their applications, there is an increasing demand for efficient and secure authentication mechanisms to protect against unauthorized access. Traditional authentication mechanisms face limitations regarding computational speed, communication costs, and vulnerability to cyber-attacks. Zero-knowledge proof (ZKP) protocols have emerged as an effective solution for achieving secure and efficient authentication in such environments without revealing sensitive information. Among ZKP protocols, $$\Sigma $$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mi>Σ</mml:mi> </mml:math> -protocols, a class of interactive ZKP protocols, have been employed for their efficiency and security. However, their interactive nature necessitates multiple rounds of communication, which can reduce efficiency and increase communication overhead for resource-constrained devices. Many works have aimed to eliminate the interaction of $$\Sigma $$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mi>Σ</mml:mi> </mml:math> -protocols by utilizing a transformation called the Fiat–Shamir transformation (FST). However, there is still a concern regarding the soundness of the FST as it can sometimes convert a secure $$\Sigma $$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mi>Σ</mml:mi> </mml:math> -protocol into an insecure non-interactive zero-knowledge (NIZK) authentication scheme. In this paper, we propose an approach for transforming $$\Sigma $$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mi>Σ</mml:mi> </mml:math> -protocols into a NIZK protocol based on the FST, yielding significant enhancements in efficiency, communication overhead reduction, and elimination of interaction. Our proposed protocol enables the completion of the authentication process in a single request while also strengthening the soundness of $$\Sigma $$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mi>Σ</mml:mi> </mml:math> -protocols in comparison with the traditional FST by requiring two authentication factors instead of one. To demonstrate our approach’s robustness, we conducted comprehensive informal and formal security analyses (using the Tamarin-Prover). Our protocol demonstrated completeness, soundness, zero-knowledge properties, and robustness against attacks, including eavesdropping, message modification, replay, and brute force attacks. Additionally, our performance analysis displayed a remarkable 50% improvement in computational cost compared to traditional $$\Sigma $$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mi>Σ</mml:mi> </mml:math> -protocols, underscoring its efficiency for practical use.

Xiao Chen, Zibin Zheng, Weiqi Dai, Yanchun Sun · 6 authors

No abstract is available for this record.

Authors unavailable

A zeroknowledge proof is a game between a prover and a verifier, where the aim of the prover is to present the correctness of an assertion without giving the actual proof. This enables systems to achieve privacy with transparency and, if required, compliance. Zero knowledge proofs have been used in protection of data in healthcare and other systems, anonymous verifiable voting, financial systems like digital currencies, secure exchange of digital assets, secure remote biometric authentication, secure auction, and blockchain. The challenge of zero-knowledge proofs is that they are computationally hard to produce, some implementations need a trusted third party for setup and system initialization, some require efficiency optimization methods. Moreover, common algorithms cannot resist quantum computing attacks warranting research in the area.

Salna Joy, Baby Chithra R, P S Neethu, Anju M. I · 7 authors

The healthcare sector deals with extremely sensitive information that must be administered in a safe and confidential way. The objective of the proposed framework is to utilize Blockchain Technology (BT) for tracking medical prescriptions and the implementation is carried out using the Hyperledger Fabric platform, an enterprise-grade open-source distributed ledger technology platform designed for Bigdata applications. Multiple entities, including patients, e-pharmacies, pharmacies, doctors and hospitals can establish connections by introducing several nodes in the Fabric chain. A web-centered application is provided for doctors, connecting them with participating pharmacies, hospitals and e-pharmacies through which, they can share patient prescription. Pharmacies and e-pharmacies have access to this data and can notify patients about the availability of prescribed medicines. Additionally, reminders for refills, such as heart medication, can be sent for patients requiring long-term medication. Patients can also try with nearby pharmacies and the availability of their prescribed medicines. The inclusion of a wallet feature in the application enables patients to use mobile tokens for making purchases. Patient data is treated with the utmost confidentiality, kept private, and accessed only upon request and with the consent of the concerned parties. This privacy is ensured through the use of zero-knowledge proof. Patients retain access to their complete medical history, facilitating interactions with doctors without the need for repetitive information sharing.

Shashank Saroop

In recent years, the increasing prevalence of digital transactions and data sharing has underscored the critical importance of privacy and security in the digital realm. Blockchain technology, initially designed to support cryptocurrencies like Bitcoin, has evolved into a versatile platform with the potential to provide trust, transparency, and data immutability in a wide range of applications. Concurrently, zero-knowledge proofs have emerged as a pioneering approach to safeguarding data privacy, allowing parties to validate information without disclosing the underlying data. This review paper thoroughly investigates the convergence of blockchain technology and zero-knowledge proofs, aiming to understand how their synergy can foster privacy-preserving transactions. We examine the foundational principles of zero-knowledge proofs, their theoretical underpinnings, and practical implementation within blockchain networks. Through a comprehensive analysis, we assess the effectiveness of this amalgamation in protecting sensitive data and consider its applicability to diverse use cases. This review provides a detailed exploration of the synergistic potential of blockchain and zero-knowledge proofs in reshaping the landscape of data privacy in an increasingly interconnected world.

Shobha Tyagi, Shobha Tyagi

The Zcash cryptocurrency is the first well-known application of zk-SNARKs in the blockchain. The role of Zk-SNARK is to provide privacy and confidentiality. As blockchain is incapable of providing privacy in the blockchain system, the researchers are banking at Zero Knowledge Proof protocols as the solution to the privacy problem. The Zero Knowledge Proof is a relatively new technique. Hence, currently, it comes with many risks and vulnerabilities. This paper mentions risks in cryptocurrency with Zero Knowledge Proof, primarily of Zcash. The discussed vulnerabilities are information leakage in transactions, trust risk, implementation vulnerability, and other security issues.

Huayi Qi, Minghui Xu, Dongxiao Yu, Xiuzhen Cheng

The privacy concern in smart contract applications continues to grow, leading to the proposal of various schemes aimed at developing comprehensive and universally applicable privacy-preserving smart contract (PPSC) schemes. However, the existing research in this area is fragmented and lacks a comprehensive system overview. This paper aims to bridge the existing research gap on PPSC schemes by systematizing previous studies in this field. The primary focus is on two categories: PPSC schemes based on cryptographic tools like zero-knowledge proofs, as well as schemes based on trusted execution environments. In doing so, we aim to provide a condensed summary of the different approaches taken in constructing PPSC schemes. Additionally, we also offer a comparative analysis of these approaches, highlighting the similarities and differences between them. Furthermore, we shed light on the challenges that developers face when designing and implementing PPSC schemes. Finally, we delve into potential future directions for improving and advancing these schemes, discussing possible avenues for further research and development.

Said A. Salloum, Khalaf Tahat, Dina Tahat, Ahmed Mansoori · 5 authors

In the burgeoning Metaverse, an intricate digital realm sculpted by the convergence of physical virtual reality and enduring virtual spaces, there lies unprecedented potential for revolutionary social and economic interactions. However, despite its growing influence in our daily lives, there exists a notable research gap: a comprehensive understanding of the security and privacy facets inherent to the Metaverse. This study endeavors to bridge this gap by examining the pivotal dimensions of security and privacy within this nascent domain. As the distinctions between physical and digital realms fade, comprehending and addressing vulnerabilities becomes vital to preempt threats and uphold individual freedoms. Our findings elucidate not only the continuous threats, such as unauthorized data breaches and virtual reality hardware susceptibilities but also spotlight promising countermeasures. The utility of blockchain for decentralized identity protection and zero-knowledge proofs for enhancing transactional privacy without excessive data exposure are exemplary solutions. Additionally, the emergence of AI-driven security offers the potential for defenses that adapt to shifting threats. Yet, relying exclusively on technological innovations is insufficient. The Metaverse's enduring success and safety rest on a symbiotic relationship among technology, regulatory frameworks, and informed user participation. This requires developers to be proactive in integrating security, regulators to formulate and enforce robust standards, and users to stay vigilant. To conclude, the Metaverse, with its transformative potential, can only flourish within a trustworthy and secure environment. It necessitates a collaborative effort from all stakeholders to foster a Metaverse that truly enriches, empowers, and connects users in this expansive digital landscape.

Alex Berke, Tobin South, Robert Mahari, Kent Larson · 5 authors

Tax returns contain key financial information of interest to third parties: public officials are asked to share financial data for transparency, companies seek to assess the financial status of business partners, and individuals need to prove their income to landlords or to receive benefits. Tax returns also contain sensitive data such that sharing them in their entirety undermines privacy. We introduce a zero-knowledge tax disclosure system (zkTax) that allows individuals and organizations to make provable claims about select information in their tax returns without revealing additional information, which can be independently verified by third parties. The system consists of three distinct services that can be distributed: a tax authority provides tax documents signed with a public key; a Redact &amp; Prove Service enables users to produce a redacted version of the tax documents with a zero-knowledge proof attesting the provenance of the redacted data; a Verify Service enables anyone to verify the proof. We implement a prototype with a user interface, compatible with U.S. tax forms, and demonstrate how this design could be implemented with minimal changes to existing tax infrastructure. Our system is designed to be extensible to other contexts and jurisdictions. This work provides a practical example of how distributed tools leveraging cryptography can enhance existing government or financial infrastructures, providing immediate transparency alongside privacy without system overhauls.

Yong Zhao, Shaojun Yang, Xinyi Huang

No abstract is available for this record.

John Bostanci, Luowen Qian, Nicholas Spooner, Henry Yuen

We prove a tight parallel repetition theorem for $3$-message computationally-secure quantum interactive protocols between an efficient challenger and an efficient adversary. We also prove under plausible assumptions that the security of $4$-message computationally secure protocols does not generally decrease under parallel repetition. These mirror the classical results of Bellare, Impagliazzo, and Naor [BIN97]. Finally, we prove that all quantum argument systems can be generically compiled to an equivalent $3$-message argument system, mirroring the transformation for quantum proof systems [KW00, KKMV07]. As immediate applications, we show how to derive hardness amplification theorems for quantum bit commitment schemes (answering a question of Yan [Yan22]), EFI pairs (answering a question of Brakerski, Canetti, and Qian [BCQ23]), public-key quantum money schemes (answering a question of Aaronson and Christiano [AC13]), and quantum zero-knowledge argument systems. We also derive an XOR lemma [Yao82] for quantum predicates as a corollary.

Sheng Peng, Di Sun, Linkai Zhu, Hongtu Zhou · 6 authors

The rise of digital globalization necessitates robust cross-border data sharing mechanisms, presenting challenges in security, privacy, and regulatory compliance. This paper introduces a novel blockchain-based framework to address these challenges, facilitating secure and efficient data exchange while meeting diverse international compliance requirements. Our approach combines advanced cryptographic techniques with smart contracts to create a dual-layered blockchain architecture. The first layer provides participant anonymity through zero-knowledge proofs, and the second ensures traceable, compliant data transactions. This solution streamlines compliance with varied data protection laws, offering a transparent and privacy-preserving platform for global data sharing initiatives. It promises significant benefits for entities engaged in multinational operations, enhancing security, simplifying regulatory adherence, and protecting user privacy.

Bingxue Zhang, Guangguang Lu, Pengpeng Qiu, Xumin Gui · 5 authors

Federated learning, as one of the three main technical routes for privacy computing, has been widely studied and applied in both academia and industry. However, malicious nodes may tamper with the algorithm execution process or submit false learning results, which directly affects the performance of federated learning. In addition, learning nodes can easily obtain the global model. In practical applications, we would like to obtain the federated learning results only by the demand side. Unfortunately, no discussion on protecting the privacy of the global model is found in the existing research. As emerging cryptographic tools, the zero-knowledge virtual machine (ZKVM) and homomorphic encryption provide new ideas for the design of federated learning frameworks. We have introduced ZKVM for the first time, creating learning nodes as local computing provers. This provides execution integrity proofs for multi-class machine learning algorithms. Meanwhile, we discuss how to generate verifiable proofs for large-scale machine learning tasks under resource constraints. In addition, we implement the fully homomorphic encryption (FHE) scheme in ZKVM. We encrypt the model weights so that the federated learning nodes always collaborate in the ciphertext space. The real results can be obtained only after the demand side decrypts them using the private key. The innovativeness of this paper is demonstrated in the following aspects: 1. We introduce the ZKVM for the first time, which achieves zero-knowledge proofs (ZKP) for machine learning tasks with multiple classes and arbitrary scales. 2. We encrypt the global model, which protects the model privacy during local computation and transmission. 3. We propose and implement a new federated learning framework. We measure the verification costs under different federated learning rounds on the IRIS dataset. Despite the impact of homomorphic encryption on computational accuracy, the framework proposed in this paper achieves a satisfactory 90% model accuracy. Our framework is highly secure and is expected to further improve the overall efficiency as cryptographic tools continue to evolve.

Sylvain Chatel, Christian Mouchet, Ali Utkan Şahin, Apostolos Pyrgelis · 6 authors

Multiparty fully homomorphic encryption (MFHE) schemes enable multiple parties to efficiently compute functions on their sensitive data while retaining confidentiality. However, existing MFHE schemes guarantee data confidentiality and the correctness of the computation result only against honest-but-curious adversaries. In this work, we provide the first practical construction that enables the verification of MFHE operations in zero-knowledge, protecting MFHE from malicious adversaries. Our solution relies on a combination of lattice-based commitment schemes and proof systems which we adapt to support both modern FHE schemes and their implementation optimizations. We implement our construction in PELTA. Our experimental evaluation shows that PELTA is one to two orders of magnitude faster than existing techniques in the literature.

Yibin Yang, David Heath, Carmit Hazay, Vladimir Kolesnikov · 5 authors

Vector Oblivious Linear Evaluation (VOLE) supports fast and scalable interactive Zero-Knowledge (ZK) proofs. Despite recent improvements to VOLE-based ZK, compiling proof statements to a control-flow oblivious form (e.g., a circuit) continues to lead to expensive proofs. One useful setting where this inefficiency stands out is when the statement is a disjunction of clauses \mathcalL _1 łor \cdots łor \mathcalL _B. Typically, ZK requires paying the price to handle all B branches. Prior works have shown how to avoid this price in communication, but not in computation.