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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.
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.
Consensus algorithms are applied in the context of distributed computer systems to improve their fault tolerance. The explosive development of distributed ledger technology following the proposal of “Bitcoin” led to a sharp increase in research activity in this area. Specifically, public and permissionless networks require robust leader selection strategies resistant to Sybil attacks in which malicious attackers present bogus identities to induce byzantine faults. Our goal is to analyse the entire breadth of works in this area systematically, thereby uncovering trends and research directions regarding Sybil attack resistance in today’s blockchain systems to benefit the designs of the future. Through a systematic literature review, we condense an immense set of research records (N = 21,799) to a relevant subset (N = 483). We categorise these mechanisms by their Sybil attack resistance characteristics, leader selection methodology, and incentive scheme. Mechanisms with strong Sybil attack resistance commonly adopt the principles underlying “Proof-of-Work” or “Proof-of-Stake” while mechanisms with limited resistance often use reputation systems or physical world linking. We find that only a few fundamental paradigms exist that can resist Sybil attacks in a permissionless setting but discover numerous innovative mechanisms that can deliver weaker protection in system scenarios with smaller attack surfaces.
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