Preserving privacy in blockchain-based systems is crucial for ensuring anonymity and confidentiality during transactions. While cryptographic solutions can address on-chain privacy concerns, their implementation on blockchains may introduce performance overhead, which remains unclear to researchers and practitioners. This paper investigates the performance impact of integrating zero-knowledge proofs (ZKPs) into the widely adopted permissioned blockchain framework called Hyperledger Fabric. The study focuses on evaluating the scalability and bottleneck aspects of blockchain platforms incorporating ZKPs. Through comprehensive experimentation and analysis, the study reveals that the integration of ZKPs compromises performance in terms of transaction rates and latency, while effectively safeguarding users' personal information. Implementing on-chain ZKP feature would result in a performance loss of 30% to 87.5% in various experimental configurations in Hyperledger Fabric. The findings presented in this paper are informative for the design and implementation of blockchain-based systems with strict privacy requirements.@en

The emergence of blockchain technologies has created the possibility of transforming business processes in the form of immutable agreements called smart contracts. Smart contracts suffer from a major limitation; they cannot authenticate the trustworthiness of real-world data sources, creating the need for intermediaries called oracles. Oracles are trusted entities that connect on-chain systems with off-chain data, allowing smart contracts to operate on real-world inputs in a trustworthy manner. A popular oracle protocol is a crowdsourced oracle, where unrelated individuals attest to facts through voting mechanisms in smart contracts. Crowdsourced oracles have unique challenges: the trustworthiness and correctness of outcomes cannot be explicitly verified. These problems are aggravated by inherent vulnerabilities to attacks, such as Sybil attacks. To address this weakness, this paper proposes a reputation-based mechanism, where oracles are given a reputation value depending on the implied correctness of their actions over time. This reputation score is used to eliminate malicious agents from the participant pool. Additionally, two reputation-based voting mechanisms are proposed. The effectiveness of the proposed mechanism is evaluated using an agent-based simulation of a crowdsourced oracle platform, where a pool of oracles performs evaluate Boolean queries.

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Traditional cloud Service Level Agreement (SLA) suffers from lacking a trustworthy platform for automatic enforcement. The emerging blockchain technique brings in an immutable solution for tracking transactions among business partners. However, it is still very challenging to prove the credibility of possible violations in the SLA before recording them onto the blockchain. To tackle this challenge, we propose a witness model using game theory and the smart contract techniques. The proposed model extends the existing service model with a new role called 'witness' for detecting and reporting service violations. Witnesses gain revenue as an incentive for performing these duties, and the payoff function is carefully designed in a way that trustworthiness is guaranteed: in order to get the maximum profit, the witness has to always tell the truth. This is analyzed and proved through game theory using the Nash equilibrium principle. In addition, an unbiased sortition algorithm is proposed to ensure the randomness of the independent witnesses selection from the decentralized witness pool, to avoid possible unfairness or collusion. An auditing mechanism is also introduced in the paper to detect potential irrational or malicious witnesses. We have prototyped the system leveraging the smart contracts of Ethereum blockchain. Experimental results demonstrate the feasibility of the proposed model and indicate good performance in accordance with the design expectations.

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