Blockchain Papers

Joel Sousa, Emerson B. Tomaz, Allysson Allex Araújo

Authenticity represents an essential facet of information security explored across various Information Systems (IS), including Internet of Things (IoT) devices in Industry 4.0. However, deploying authentication mechanisms in specific IoT devices poses significant challenges, particularly for those with energy, memory, and computational power constraints. Given this context, this ongoing research project aims to compare conventional authentication mechanisms for low-resource IoT devices and identify the most efficient one among them. As an initial result, this paper aims to present our methodological scope and discuss preliminary empirical results derived from a computational experiment using the Non Interactive Zero Knowledge Proofs (NIZKP), algorithm in Arduino Nano. This research seeks to enhance the comprehension of authentication mechanisms in low-resource IoT devices, thus facilitating better decision-making processes in IS settings and contributing to academia and practice.

Marco Stronati, Denis Firsov, Antonio Locascio, Benjamin Livshits

Plonkish is a popular circuit format for developing zero-knowledge proof systems that powers a number of major projects in the blockchain space, responsible for holding billions of dollars and processing millions of transactions per day. These projects, including zero-knowledge rollups, rely on highly hand-optimized circuits whose correctness comes at the cost of time-consuming testing and auditing. In this paper, we present Clap, the first Rust eDSL with a proof system agnostic circuit format, facilitating extensibility, automatic optimizations, and formal assurances for the resultant constraint system. Clap casts the problem of producing Plonkish constraint systems and their witness generators as a semantic-preserving compilation problem. Soundness and completeness of the transformation guarantees the absence of subtle bugs caused by under- or over-constraining. Our experimental evaluation shows that its automatic optimizations achieve better performance compared to manual circuit optimization. The optimizer can also be used to automatically derive custom gates from circuit descriptions.

Daniel Commey, Sena Hounsinou, Garth V. Crosby

This paper presents a framework for securing blockchain-based IoT systems by integrating Physical Unclonable Functions (PUFs) and Zero-Knowledge Proofs (ZKPs) within a Hyperledger Fabric environment. Our approach leverages PUFs for robust device authentication and ZKPs for privacy-preserving transaction processing, addressing key challenges of security, privacy, and scalability in IoT systems. The framework’s architecture utilizes Hyperledger Fabric’s modular design and private channels to enhance scalability. Off-chain experimental results demonstrate the framework’s feasibility, with compact proof sizes (median 805 bytes) and efficient processing times (average 2,800 ms end-to-end). A comprehensive security analysis shows the framework’s resilience against various attacks, including device impersonation and data tampering. This work provides a foundation for secure and scalable blockchain-based IoT systems, with directions for future on-chain implementation and optimization for resource-constrained devices.

Shaoqi Yuan, Wenzhong Yang, Xiaodan Tian, Wenjie Tang

With the continuous advancement of information technology, a growing number of works, including articles, paintings, and music, are being digitized. Digital content can be swiftly shared and disseminated via the Internet. However, it is also vulnerable to malicious plagiarism, which can seriously infringe upon the rights of creators and dampen their enthusiasm. To protect creators’ rights and interests, a sophisticated method is necessary to authenticate digital intellectual property rights. Traditional authentication methods rely on centralized, trustworthy organizations that are susceptible to single points of failure. Additionally, these methods are prone to network attacks that can lead to data loss, tampering, or leakage. Moreover, the circulation of copyright information often lacks transparency and traceability in traditional systems, which leads to information asymmetry and prevents creators from controlling the use and protection of their personal information during the authentication process. Blockchain technology, with its decentralized, tamper-proof, and traceable attributes, addresses these issues perfectly. In blockchain technology, each node is a peer, ensuring the symmetry of information. However, the transparent feature of blockchains can lead to the leakage of user privacy data. Therefore, this study designs and implements an Ethereum blockchain-based intellectual property authentication scheme with privacy protection. Firstly, we propose a method that combines elliptic curve cryptography (ECC) encryption with digital signatures to achieve selective encryption of user personal information. Subsequently, an authentication algorithm based on Zero-Knowledge Succinct Non-Interactive Argument of Knowledge (zk-SNARK) is adopted to complete the authentication of intellectual property ownership while encrypting personal privacy data. Finally, we adopt the InterPlanetary File System (IPFS) to store large files, solving the problem of blockchain storage space limitations.

Stephan Rau, Alexander Rau, Johanna Nattenmüller, Anna Maria Fink · 7 authors

BACKGROUND: We investigated the potential of an imaging-aware GPT-4-based chatbot in providing diagnoses based on imaging descriptions of abdominal pathologies. METHODS: Utilizing zero-shot learning via the LlamaIndex framework, GPT-4 was enhanced using the 96 documents from the Radiographics Top 10 Reading List on gastrointestinal imaging, creating a gastrointestinal imaging-aware chatbot (GIA-CB). To assess its diagnostic capability, 50 cases on a variety of abdominal pathologies were created, comprising radiological findings in fluoroscopy, MRI, and CT. We compared the GIA-CB to the generic GPT-4 chatbot (g-CB) in providing the primary and 2 additional differential diagnoses, using interpretations from senior-level radiologists as ground truth. The trustworthiness of the GIA-CB was evaluated by investigating the source documents as provided by the knowledge-retrieval mechanism. Mann-Whitney U test was employed. RESULTS: The GIA-CB demonstrated a high capability to identify the most appropriate differential diagnosis in 39/50 cases (78%), significantly surpassing the g-CB in 27/50 cases (54%) (p = 0.006). Notably, the GIA-CB offered the primary differential in the top 3 differential diagnoses in 45/50 cases (90%) versus g-CB with 37/50 cases (74%) (p = 0.022) and always with appropriate explanations. The median response time was 29.8 s for GIA-CB and 15.7 s for g-CB, and the mean cost per case was $0.15 and $0.02, respectively. CONCLUSIONS: The GIA-CB not only provided an accurate diagnosis for gastrointestinal pathologies, but also direct access to source documents, providing insight into the decision-making process, a step towards trustworthy and explainable AI. Integrating context-specific data into AI models can support evidence-based clinical decision-making. RELEVANCE STATEMENT: A context-aware GPT-4 chatbot demonstrates high accuracy in providing differential diagnoses based on imaging descriptions, surpassing the generic GPT-4. It provided formulated rationale and source excerpts supporting the diagnoses, thus enhancing trustworthy decision-support. KEY POINTS: • Knowledge retrieval enhances differential diagnoses in a gastrointestinal imaging-aware chatbot (GIA-CB). • GIA-CB outperformed the generic counterpart, providing formulated rationale and source excerpts. • GIA-CB has the potential to pave the way for AI-assisted decision support systems.

Chenhao Shi, Ruibang Liu, H. B. Chen, Guoqiang Li · 5 authors

The communities of blockchains and distributed ledgers have been stirred up by the introduction of zero-knowledge proofs (ZKPs). Originally designed as a solution to privacy issues, ZKPs have now evolved into an effective remedy for scalability concerns. To enable ZKPs, Rank-1 Constraint Systems (R1CSs) offer a verifier for bilinear equations. In order to accurately and efficiently represent R1CSs, several language tools, such as Circom, Noir, and Snarky, have been proposed to automate the compilation of advanced programs into R1CSs. However, due to the flexible nature of R1CS representation, there can be significant differences in the compiled R1CS forms generated from circuit language programs with the same underlying semantics. To address this issue, this article puts forth a dataflow-based R1CS paradigm algorithm, which produces a standardized format for different R1CS instances with identical semantics. Additionally, we present an R1CS benchmark, and our experimental evaluation demonstrates the efficacy of our methods.

Robert G. Werner, Dominique Briechle, Marit Elke Anke Mathiszig

Currently, the ad hoc, one-way distribution of pharmaceuticals from pharmacies to their customers is inefficient and high in emissions. The HitchhikeBox concept aims to improve the current logistics system by utilizing existing transport channels. This eliminates the need for single-purpose delivery trips and personnel. The system is open to competing service providers, with fully automated contract management, payment and sanctioning of the parties involved. The system utilizes asymmetric encryption and zero-knowledge proofs to guarantee user privacy and non-traceability of deliveries for contracts, payments, and sensor data. The system is designed to be resilient, self-governing and suitable for highly sensitive goods, such as the transport of pharmaceuticals, by ensuring their optimal condition. In addition, the system utilizes smart contracts to conclude and enforce contracts, as well as a distributed off-chain cluster to process and store data in a GDPR-compliant manner. The HitchhikeBox concept facilitates semi-automated, cost-effective and eco-friendly logistics while maintaining reliability, privacy and liability.

Timothé Albouy, Emmanuelle Anceaume, Davide Frey, Mathieu Gestin · 7 authors

This article introduces a new asynchronous Byzantine-tolerant asset transfer system (cryptocurrency) with three noteworthy properties: quasi-anonymity, lightness, and consensus-freedom. Quasi-anonymity means no information is leaked regarding the receivers and amounts of the asset transfers. Lightness means that the underlying cryptographic schemes are \textit{succinct}, and each process only stores data polylogarithmic in the number of its own transfers.Consensus-freedom means the system does not rely on a total order of asset transfers. The proposed algorithm is the first asset transfer system that simultaneously fulfills all these properties in the presence of asynchrony and Byzantine processes. To obtain them, the paper adopts a modular approach combining a new distributed object called agreement proofs and well-known techniques such as vector commitments, universal accumulators, and zero-knowledge proofs. The paper also presents a new non-trivial universal accumulator implementation that does not need knowledge of the underlying accumulated set to generate (non-)membership proofs, which could benefit other crypto-based applications.

Michael Sober, Giulia Scaffino, Stefan Schulte

The closed architecture of prevailing blockchain systems renders the usage of this technology mostly infeasible for a wide range of real-world problems. Most blockchains trap users and applications in their isolated space without the possibility of cooperating or switching to other blockchains. Therefore, blockchains need additional mechanisms for seamless communication and arbitrary data exchange between each other and external systems. Unfortunately, current approaches for cross-blockchain communication are resource-intensive or require additional blockchains or tailored solutions depending on the applied consensus mechanisms of the connected blockchains. Therefore, we propose an oracle with an off-chain aggregation mechanism based on Zero-Knowledge Succinct Non-interactive Arguments of Knowledge (zk-SNARKs) to facilitate cross-blockchain communication. The oracle queries data from another blockchain and applies a rollup-like mechanism to move state and computation off-chain. The zkOracle contract only expects the transferred data, an updated state root, and proof of the correct execution of the aggregation mechanism. The proposed solution only requires constant 378 kgas to submit data on the Ethereum blockchain and is primarily independent of the underlying technology of the queried blockchains.

Alexandr Kuznetsov, Alex Rusnak, Anton Yezhov, Dzianis Kanonik · 6 authors

Zero-knowledge proofs have emerged as a powerful tool for enhancing privacy and security in blockchain applications. However, the efficiency and scalability of proof systems remain a significant challenge, particularly in the context of Merkle tree inclusion proofs. Traditional proof aggregation techniques based on AND logic suffer from a high verification complexity and data communication overhead, limiting their practicality for large-scale applications. In this paper, we propose a novel proof aggregation approach based on OR logic, which enables the generation of compact and universally verifiable proofs for Merkle tree inclusion. By adapting and extending the concept of OR composition from Sigma protocols, we achieve a proof size that is independent of the number of leaves in the tree, and verification can be performed using any single valid leaf hash. This represents a significant improvement over AND aggregation, which requires the verifier to process all leaf hashes. We formally define the OR aggregation logic; describe the process of generating universal proofs; and provide a comparative analysis that demonstrates the advantages of our approach in terms of proof size, verification data, and universality. Furthermore, we discuss the potential of combining OR and AND aggregation logics to create complex acceptance functions, enabling the development of expressive and efficient proof systems for various blockchain applications. The proposed techniques have the potential to significantly enhance the scalability, efficiency, and flexibility of zero-knowledge proof systems, paving the way for more practical and adaptive solutions in large-scale blockchain ecosystems.

Jie Li, Yuanyuan Lin, Yibing Li, Yan Zhuang · 5 authors

The Internet of Vehicles (IoV) connects an isolated individual on the road to share information, which can improve traffic efficiency. However, the promotion of information sharing brings the critical security issues of identity authentication, followed by privacy protection issues in the authentication process in the IoV. In this study, we designed a blockchain-based conditional privacy-preserving authentication scheme for the IoV (BPA). Our scheme implements zero-knowledge proof (ZKP) to verify the identities of vehicles, which moves the authentication process down to the Roadside Units (RSUs) and achieves decentralized authentication at the edge nodes. Moreover, blockchain technology is utilized to synchronize a consistent ledger across all RSUs for recording and disseminating vehicle authentication states, which enhances the overall authentication process efficiency. We provide a theoretical analysis asserting that the BPA ensures enhanced security and effectively protects the privacy of all participating vehicles. Experimental evaluations confirm that our scheme outperforms existing solutions in terms of the computational and communication overhead.

Jesús García-Rodríguez, Stephan Krenn, Jorge Bernal Bernabé, Antonio Skármeta

The increasing user awareness and regulatory framework (e.g., GDPR, eIDAS2) have contributed to considering data minimization and privacy-by-design as central guiding principles for new systems. Among others, this has led to a paradigm shift towards Self-Sovereign Identity solutions to put the user in full control over their data. Despite the promising landscape, privacy-preserving Attribute-Based Credentials (p-ABC) have not been widely adopted, mainly due to the lack of secure, flexible and efficient implementations that cover the basic and advanced needs in p-ABC systems. In this work, we tackle this gap by developing an improved zero-knowledge showing protocol of a distributed p-ABC scheme based on Pointcheval-Sanders Multi-Signatures to allow for modular extensions through commit-and-prove techniques. We use it to implement a flexible p-ABC system with decentralized issuance that, apart from the basic notions of p-ABCs, covers range proofs, pseudonyms, inspection and revocation. Lastly, we thoroughly evaluate the performance of the system under different testbed conditions, showing a significant efficiency improvement over previous implementations.

Marcos Portnoi

When a user wants to access certain services offered by a service provider, typically the user must first authenticate herself with the service provider, such that the service provider may grant authorization to access the services. Authentication is the process through which the user provides confirmation of her identity to the service provider (and, in parallel, the user should receive confirmation that the service provider is legitimate). Several types (or factors) of authenticators can be utilized in this process. Namely, things the user know (e.g.: passwords, PINs); things the user possesses (e.g., token authenticators in the smartphone, key fobs, cards); characteristics or physical traits of the user (e.g., fingerprint, iris pattern); and, as proposed in this dissertation, the user’s location. Each authentication factor has, in terms of security and user experience when compared to other factors, strong and weak aspects, (or pros and cons). For instance, passwords must be long and random, but then remembering them can be taxing; fingerprints are (believed to be) unique and thus form a good authenticator, but they are immutable and hardly confidential; token authenticators and out-of-band tokens (such as SMS tokens) provide an ephemeral value that is valuable for security, but the user might lose possession of the respective token device. Combining two or more of those authenticators results in a potential increased security as compared to utilizing only one authenticator, which is known as multi-factor authentication. ☐ This dissertation focuses on multi-factor authentication. I present a cryptographic method to enable location as an authentication factor, using the flexibility of Ciphertext-Policy Attribute-Based Encryption (CP-ABE) and its access policies, together with location beacons. Such that this location authenticator can be realized, I develop a technique to request and control the presentation of multi-factor authenticators, through which scores are assigned to each authenticator type and both the user and the authentication service are aware of a minimum score needed for full authentication. To address the necessity of a secure scheme through which a user presents the authenticators, I construct a method for conveying the authentication factors in a Zero-Knowledge Password Proof (ZKPP) scheme and through an ephemeral, confidential session. The method also provides a secure joint authenticator that is the cryptographic composite (built within ZKPP) of the individual authenticators. To embody and realize these techniques, I devise a multi-factor authentication protocol named LOCATHE, through which a user device or user can authenticate herself to an authentication service using the device’s or user’s location and other authentication factors, with guarantees of forward secrecy. Moreover, I design a Location-Enhanced Multi-Factor Authentication Service (Loc-Auth), abstracting hardware (such as the location beacons) and control into a layered structure, to provide the authentication services and support for the components of this dissertation. Finally, I develop a Proof-of-Concept system, and perform an extensive security evaluation and analysis of the work herein.

António Pesqueira, Maria José Sousa, Andréia de Bem Machado

Blockchain technology (BT), originally developed to facilitate secure digital monetary transactions, has recently gained significant traction in various healthcare sectors. Characterized by the exponential growth of sensitive data, the healthcare sector is poised to witness the emergence of BT. This emergence is primarily driven by the pressing need to globally expose, protect against threats, ensure confidentiality, and establish traceability for the plethora of sensitive data continuously generated by the healthcare industry. The healthcare supply chain focuses on traceability due to the prevalence of counterfeit and recalled drugs. Managing operational constraints such as temperature, humidity, and air quality within specified parameters is paramount. The various processes involved in international trade transactions contribute to the creation of numerous records, each of which is meticulously entered into the systems of the companies involved. Therefore, the problem set for this study was: What are the challenges and prospects for BT in the healthcare sector? To answer this question, the following objective was set: describe and examine the challenges and prospects of BT in the healthcare sector. In addition, a key research objective was to identify specific applications and use cases that can benefit the most from this technological advancement. In line with the research objective, a systematic review of all studies BT for traceability, anti-counterfeiting, and fraud detection was conducted from January 2023 to September 2023. Using robust tools such as VosViewer, we used bibliometric metrics from the renowned medical repository PubMed to construct and visually represent data analysis networks. BT shows remarkable potential to improve traceability and optimize supply chain management within healthcare organizations. The study includes a deep analysis of blockchain capabilities, including smart contracts, identity management, access control, and zero-knowledge proofing.

Zihou Zhang, Jiangtao Li, Yufeng Li, Yuanhang He

Edge computing provides higher computational power and lower transmission latency by offloading tasks to nearby edge nodes with available computational resources to meet the requirements of time-sensitive tasks and computationally complex tasks. Resource allocation schemes are essential to this process. To allocate resources effectively, it is necessary to attach metadata to a task to indicate what kind of resources are needed and how many computation resources are required. However, these metadata are sensitive and can be exposed to eavesdroppers, which can lead to privacy breaches. In addition, edge nodes are vulnerable to corruption because of their limited cybersecurity defenses. Attackers can easily obtain end-device privacy through unprotected metadata or corrupted edge nodes. To address this problem, we propose a metadata privacy resource allocation scheme that uses searchable encryption to protect metadata privacy and zero-knowledge proofs to resist semi-malicious edge nodes. We have formally proven that our proposed scheme satisfies the required security concepts and experimentally demonstrated the effectiveness of the scheme.

Lun Xu, Yun Li, Ru Jia, Beibei Wang

In the backdrop of advancing communication technology and the adoption of decarbonization initiatives, peer-to-peer (P2P) electricity trading has evolved into a consequential avenue for the reliable utilization of clean energy resources. Most efforts have focused on the design of P2P distributed mechanisms to ensure that the security constraints of the grid can be adhered to. However, ensuring the assurance of the correct operation of the distributed mechanisms is also essential but has received less attention. A common assumption is that all participants in the P2P market are honest and make reasonable bids at market prices. Such an assumption could be risky because the P2P market clearing process relies on a coordination process of market participants and the clearing outcome of the P2P market is susceptible to manipulation by dishonest participants. In this work, we propose a new architecture for the P2P market by adding a verification layer based on zero-knowledge proof technology to identify dishonest bidding information of market participants without collecting their private cost information. In addition, we introduce an asynchronous market mechanism, which can greatly guide the P2P market clearing results in a dishonest environment to be close to the theoretical optimal results. Case studies demonstrate the advantages of our approach in resisting dishonesty, preserving privacy, and enhancing market robustness, which can help build a more credible and resilient P2P market environment.

Salman Saleem Virani

Abstract The focus of this review article is on the societal problems and end user acceptance of blockchain technology. The paper begins by outlining the importance of blockchain in modernizing trust and data management systems and highlighting its rapid spread across numerous industries. In‐depth analysis of the adoption‐influencing aspects is done, which also lists the advantages and typical end‐user problems. It examines the privacy implications, restrictions on pseudonymity, and function of technologies that improve privacy, such as zero‐knowledge proofs, while also exploring the legal and regulatory environment around blockchain, putting a focus on digital identity, intellectual property, and data ownership. It also evaluates blockchain security features, such as flaws and risks associated with smart contracts, discusses best practices for boosting security, discusses the societal effects of blockchain, and makes suggestions for legislators, companies, and scholars. The use of blockchain technology and its effects on privacy, rights, and security are discussed in real‐world case studies as well.

Tianxiu Xie, Keke Gai, Jing Yu, Liehuang Zhu

Recent booming development of Generative Artificial Intelligence (GenAI) has facilitated model commercialization to reinforce the model performance, including licensing or trading Deep Neural Network (DNN) models. However, DNN model trading may violate the benefit of the model owner due to unauthorized replications or misuse of the model. Model identity auditing is a challenging issue in protecting DNN model ownership, and verifying the integrity and ownership of models is one of the critical obstacles. In this paper, we focus on the above issue and propose an \underline{A}ccumulator-enabled \underline{A}uditing for \underline{D}ecentralized \underline{Id}entity of DNN \underline{M}odel (A2-DIDM) that utilizes blockchain and zero-knowledge techniques to protect data and function privacy while ensuring the lightweight on-chain ownership verification. The proposed model presents a scheme of identity records via configuring model weight checkpoints with zero-knowledge proofs, which incorporates predicates to capture incremental state changes in model weight checkpoints. Our scheme ensures both computational integrity and programmability in DNN training process so that the uniqueness of the weight checkpoint sequence in a DNN model is preserved. %to ensure the correctness of model identity auditing, so that the uniqueness of the weight checkpoint sequence in a DNN model is preserved. A2-DIDM also addresses privacy protections in decentralized identity. We systematically analyze the security and robustness of our proposed model and further evaluate the effectiveness and usability of auditing DNN model identities. The code is available at https://github.com/xtx123456/A2-DIDM.git.

Akinul Islam Jony, Mubashir Mohsin

Federated learning (FL) has emerged as a viable paradigm for decentralized machine learning (DML) across multiple platforms while safeguarding data privacy.This study covers a thorough analysis of FL strategies intended to protect the privacy of data.It investigates the techniques and tactics FL uses to secure data privacy and explores the benefits and constraints of FL privacy protection.Using a methodical approach to the literature review, the study distinguishes FL approaches, explores the nuances of the FL transfer process, assesses current techniques, and identifies inherent vulnerabilities and shortcomings.These outcomes emphasize the vitality FL has for alleviating concerns about privacy while fostering collaborative learning.A variety of FL techniques are identified in the review, each of which contributes a distinct mechanism for maintaining privacy.These include differential privacy, homomorphic encryption, pruning, secure aggregation, secure multiparty computation, and zero-knowledge proofs, among others.This study provides scholars and practitioners with significant perspectives on existing procedures and prospective areas for advancement by integrating ideas from multiple sources to provide an overview of the current FL landscape concerning data privacy protection.The findings are more credible and reliable because of the systematic study, which also provides a strong basis for further research on FL and data privacy protection.At the end of the study, the implications of FL approaches for improving data privacy are covered.The significance of continuing research endeavors to tackle new problems and refine FL techniques for resilient and expandable privacy protection in the distributed machine learning age is underlined.

Student, CSE, Sir MVIT, B Sumangala, Aman Raj, Amritanshu Bhardwaj · 6 authors

Abstract - CrypticReport is a decentralized crime reporting system designed to make public reporting safer, more transparent, and free from identity risks. Citizens often avoid reporting crimes due to fear of exposure, harassment, or data misuse. CrypticReport overcomes these challenges by combining blockchain technology, decentralized IPFS storage, artificial intelligence or zero-knowledge–based authentication. Using Anon Aadhaar, users can verify their identity without revealing any personal information. AI models classify reports to block spam and detect duplicate submissions. All verified reports and evidence are stored in IPFS, and their hashes are recorded on the blockchain for tamper-proof storage. The platform uses a React interface for reporting, a Flask backend for AI processing, Ethereum smart contracts for record immutability, and the Waku protocol for real-time updates between citizens and authorities. Testing shows that the system improves trust, preserves anonymity, and ensures that no data can be altered once submitted. CrypticReport proves that decentralized systems can make crime reporting more secure, reliable, and citizen-friendly. Key Words: Blockchain, IPFS, Anonymous Reporting, AI Classification, Zero-Knowledge Proof, Decentralized Systems

Xin Liu Xin Liu, Xiaomeng Liu Xin Liu, Dan Luo Xiaomeng Liu, Gang Xu Dan Luo · 5 authors

<p>Secure multi-party computation is a hotspot in the cryptography field, and it is also a significant means to realize privacy computation. The Millionaires’ problem is the most fundamental problem among them, which is the basic module of secure multi-party computation protocols. Although there are many solutions to this problem, there are few anti-malicious adversarial protocols besides protocols based on Yao’s garbled circuit. Only a few solutions have low efficiency, and there is no protocol for rational numbers comparison under the malicious model, which restricts the solution of many secure multi-party computation problems. In this paper, the possible malicious behaviors are analyzed in the existing Millionaires’ problem protocols. These behaviors are discovered and taken precautions against through the triangle area formula, zero-knowledge proof, and cut-and-choose method, so the protocol of comparing confidentially rational numbers is proposed under the malicious model. And this paper adopts the real/ideal model paradigm to prove the security of the malicious model protocol. Efficiency analysis indicates that the proposed protocol is more effective than existing protocols. The protocol of rational numbers comparison under the malicious model is more suitable for the practical applications of secure multi-party computation, which has important theoretical and practical significance.</p> <p> </p>

Yue Zhang, Shouqiao Wang, Sijun Tan, Xiaoyuan Liu · 6 authors

This paper introduces the Proof of Sampling (PoSP) protocol, a Nash Equilibrium-based verification mechanism, and its application to decentralized machine learning inference through spML. Our protocol has a pure strategy Nash Equilibrium, compelling rational participants to act honestly. It economically disincentivizes dishonest behavior, making it costly for participants to compromise the network's integrity. In our spML protocol, we apply PoSP to decentralized inference for AI applications via a novel cryptographic protocol. The resulting protocol is much more efficient than zero knowledge proof based approaches. Moreover, we anticipate that the PoSP protocol could be effectively utilized for designing verification mechanisms within Actively Validated Services (AVS) in restaking solutions. We further expect that the PoSP protocol could be applied to a variety of other decentralized applications. Our approach enhances the reliability and efficiency of decentralized systems, paving the way for a new generation of decentralized applications.

Worasait Suwannik

Multiple sequence alignment (MSA) is a fundamental algorithm in bioinformatics. In a situation when the alignment might need to be protected while revealing the other information such the input sequences and the alignment score, zero knowledge proof can be used. In this paper, a validator checks the consistency between the input sequence and the alignment, and between the alignment and the alignment score. The validator is written in Circom language which will be compile into a circuit. Using a zero knowledge prove system called zkSNARK, a cryptographic proof is generates for the circuit and its input. This proof demonstrates that all inputs are consistent without revealing the actual alignment.

S. Sabari, N. V. Keerthana

This project focuses on Zero-Knowledge Proofs (ZKPs), a groundbreaking cryptographic technique reshaping data authentication while preserving maximum confidentiality.ZKPs enable the verification of truthfulness in statements without disclosing associated data, ensuring the utmost protection of sensitive information.With applications spanning various domains, including secure authentication protocols, privacy-preserving transactions in decentralized systems like blockchain, and confidential data verification across digital interactions, ZKPs offer versatile solutions for secure communications.The project aims to safeguard sensitive business information during outsourcing service processes.The implementation of ZKPs intends to establish a secure communication framework that fosters trust among stakeholders without compromising sensitive details, ensuring enhanced confidentiality in outsourced operations.At its core, ZKPs empower a prover to convince a verifier of a statement's validity without revealing underlying data, establishing an unmatched level of security and privacy.This concept shields against unauthorized access and data breaches, fostering trust between entities without the exchange of sensitive details.The versatility of ZKPs extends beyond authentication, influencing secure voting systems, safeguarding digital identities, and facilitating confidential transactions while upholding user privacy.