In the era of digital markets, the challenge for consumers is discerning quality amidst information asymmetry . While traditional markets use brand mechanisms to address this issue, transferring such systems to internet-based P2P markets â where misleading practices like fake ratings are rampant â remains challenging. Current internet platforms strive to counter this through verification algorithms, but these efforts find themselves in a continuous tug-of-war with counterfeit actions. Exploiting the transparency, immutability, and traceability of blockchain technology, this paper introduces a robust reputation voting system grounded in it. Unlike existing blockchain-based reputation systems, our model harnesses an intrinsically economically incentivized approach to bolster agent integrity. We optimize this model to mirror real-world user behavior , preserving the reputation systemâs foundational sustainability . Through Monte-Carlo simulations, using both uniform and power-law distributions enabled by an innovative inverse transform method, we traverse a broad parameter landscape, replicating real-world complexity. The findings underscore the promise of a sustainable, transparent, and formidable reputation mechanism. Given its structure, our framework can potentially function as a universal, sustainable oracle for offchain-onchain bridging, aiding entities in perpetually cultivating their reputation. Future integration with technologies like Ring Signature and Zero Knowledge Proof could amplify the systemâs privacy facets, rendering it particularly influential in the ever-evolving digital domain.
Business process collaboration between independent parties is challenging when participants do not completely trust each other. Tracking actions and enforcing the activity authorizations of participants via blockchain-hosted smart contracts is an emerging solution to this lack of trust, with most state-of-the-art approaches generating the orchestrating smart contract logic from Business Process Model and Notation (BPMN) models. However, compared to centralized business process orchestration services, smart contract state typically leaks potentially sensitive information about the state of the collaboration, limiting the applicability of decentralized process orchestration. This paper presents a novel, collaboration confidentiality-preserving approach where the process orchestrator smart contract only stores encrypted and hashed process states and validates participant actions against a BPMN model using zero-knowledge proofs. We cover a subset of BPMN, which is sufficient from the practical point of view, support messagepassing between participants, and provide an open-source, endto-end prototype implementation that automatically generates the key software artifacts.
Reviews and reputation scores of sellers play an important role in decision-making process of potential buyers in an e-commerce system. A trustworthy and reliable reputation system is a crucial component in the e-commerce ecosystem, as buyers rely on it to make informed decisions. In this work, we propose a privacy-preserving decentralized reputation system designed to include countermeasures against some known attacks. Our model is built on two permissioned blockchains, namely Hyperledger Indy and Hyperledger Fabric. Hyperledger Indy provides an infrastructure for implementing verifiable credentials with Zero Knowledge Proof support, which is essential for privacy preservation, while Hyperledger Fabric is a robust platform for implementing smart contracts. One of the key advantages of the proposed approach is the use of verifiable credentials for digital identities of sellers, feedback tokens issued to buyers after performing an e-commerce transaction and discount tokens issued to buyers after feedback submission. This helps to ensure that the feedback and identity information is authentic and tamper-proof, reducing the likelihood of identity-related attacks. Additionally, the collection of feedbacks and application of business rules are implemented as smart contracts on Hyperledger Fabric blockchain. This provides a secure and transparent mechanism for processing feedback, reducing the likelihood of unfair feedbacks. Overall, the proposed approach presents a robust reputation system that can help reduce identity-related attacks and unfair feedbacks. The privacy-preserving nature of the system ensures that sensitive information is protected while still enabling the verification of digital identities. The use of feedback and discount tokens incentivizes buyers to provide accurate and honest feedback, which can help reduce unfair feedbacks and identity-related attacks. Finally, the use of smart contracts ensures transparency and immutability, which enhances the overall reliability of the system.
Alex Ozdemir, Gereon Kremer, Cesare Tinelli, Clark Barrett
Abstract We study satisfiability modulo the theory of finite fields and give a decision procedure for this theory. We implement our procedure for prime fields inside the cvc5 SMT solver. Using this theory, we construct SMT queries that encode translation validation for various zero knowledge proof compilers applied to Boolean computations. We evaluate our procedure on these benchmarks. Our experiments show that our implementation is superior to previous approaches (which encode field arithmetic using integers or bit-vectors).
Anonymous cryptocurrencies are distributed applications based on blockchain technology that enhance the anonymity of user transactions. However, they also provide cover for many criminal activities. Existing traceable modifications of anonymous transaction protocols do not support public verification of the traceability of transactions, meaning dishonest users can still evade tracing by forging partial proofs. In this paper, we first propose EPoK, which is a partially extractable zero-knowledge proof scheme designed to address this issue. We provide the instantiation of EPoK, as well as its formal security proofs. Combined with EPoK and the classic anonymous transaction protocol RingCT, we propose a traceable anonymous transaction protocol TRCT for tracing participantsâ addresses and transaction amounts in anonymous transactions. Compared to previous works, TRCT is the first to implement public verification of the transactionâs traceability while still maintaining anonymity. This ensures that users cannot forge relevant proofs to evade tracing. We present and prove the security properties of TRCT, and experimentally compare its efficiency with the original RingCT protocol. The result shows that the extra overhead generated by TRCT is small.
Metaverse, the core of the next-generation Internet, is a computer-generated holographic digital environment that simultaneously combines spatio-temporal, immersive, real-time, sustainable, interoperable, and data-sensitive characteristics. It cleverly blends the virtual and real worlds, allowing users to create, communicate, and transact in virtual form. With the rapid development of emerging technologies including augmented reality, virtual reality and blockchain, the metaverse system is becoming more and more sophisticated and widely used in various fields such as social, tourism, industry and economy. However, the high level of interaction with the real world also means a huge risk of privacy leakage both for individuals and enterprises, which has hindered the wide deployment of metaverse. Then, it is inevitable to apply privacy computing techniques in the framework of metaverse, which is a current research hotspot. In this paper, we conduct comprehensive research on the necessity, taxonomy and challenges when privacy computing meets metaverse. Specifically, we first introduce the underlying technologies and various applications of metaverse, on which we analyze the challenges of data usage in metaverse, especially data privacy. Next, we review and summarize state-of-the-art solutions based on federated learning, differential privacy, homomorphic encryption, and zero-knowledge proofs for different privacy problems in metaverse. Finally, we show the current security and privacy challenges in the development of metaverse and provide open directions for building a well-established privacy-preserving metaverse system. For easy access and reference, we integrate the related publications and their codes into a GitHub repository: https://github.com/6lyc/Awesome-Privacy-Computing-in-Metaverse.git.
The paper discusses the basic principles of construction and the main types of zeroknowledge succinct non-interactive argument of knowledge (zk-SNARK) which is used in the model of a three-way insecure computing environment and based on sets of polynomials. A number of zk-SNARK cryptographic protocols with different algorithms for generating public parameters (Trusted Setup) are given, constructing succinct proofs of reliability calculations (Prover) and public/designated verification of proofs (Verifier). The cases of satisfying the feasibility of discrete functions (arithmetic/ Boolean circuits) using different polynomial sets are presented in quadratic arithmetic programs (QAP), square arithmetic programs (SAP), quadratic span programs (QSP), square span programs (SSP), quadratic polynomial programs (QPP), etc., also the use of authenticated data are described. The cryptographic transformations needed to build zk-SNARKs based on symmetric and asymmetric hash functions, exponential knowledge problems, digital signatures, homomorphic encryption, bilinear pairings based on elliptic curves, etc. are presented. Examples of multilateral verifiable calculations based on zk-SNARK are given.
Jan 1, 2023·Proceedings of the 2nd International Conference on Mathematical Statistics and Economic Analysis, MSEA 2023, May 26â28, 2023, Nanjing, China
In recent years, the business demand of international cold chain food trade has been increasing, but the process is complex, time-consuming, and there are data trust issues. This paper proposes a blockchain-based international cold chain trade platform system, which uses the immutable and traceable
Privacy plays a crucial role in the internet era, where many applications allow people to communicate and use their services through the internet. Privacy-preserving Identity Management (PPIdM) system is a scheme that helps manage usersâ identities and protects usersâ privacy by enabling users to authenticate themselves without disclosing their real identities. The PPIdM system also allows users to reveal some minor identity attributes while others remain secret selectively. However, anonymity also encourages malicious users to break the systemâs policy and commit crimes since their real identities are anonymous. Existing PPIdM systems use the identity provider (IP) as a medium to verify usersâ identity attributes, record all usersâ real identities, and ensure that malicious usersâ identities are traceable. Therefore, usersâ identities are hidden from all entities but the IP. However, the userâs privacy is vulnerable because there is nothing to guarantee that the IP is always honest and not curious about their usersâ activities and private information. This paper proposes a PPIdM system on the blockchain that helps users manage their identity attributes and keeps their real identities secret from all entities, including the IP. Still, the systemâs consensus can trace malicious usersâ real identities if they violate the systemâs policy. The PPIdMâs security requirements are analyzed and proved informally using the game-based proof scheme. The main idea of this study is to combine zk-SNARK, a type of zero-knowledge proof (ZKP), Shamirâs secret sharing (SSS), and several other cryptographic techniques.