Fair and Privacy-Preserved Data Trading Protocol by Exploiting Blockchain

【Author】 Abla, Parhat; Li, Taotao; He, Debiao; Huang, Huawei; Yu, Songsen; Zhang, Yan

【Source】IEEE TRANSACTIONS ON INFORMATION FORENSICS AND SECURITY

【影响因子】7.231

【Abstract】With the popularity of the mobile Internet, data is increasingly becoming a new resource. Therefore, the trading of such data resources has become an increasing demand. In this paper, we propose a fair privacy-preserving data trading protocol based on blockchain. Firstly, our data trading protocol achieves fairness by carefully combining the probabilistic approaches and the fully homomorphic encryption techniques. Moreover, our protocol allows online arbitration when misbehavior occurs in the trading process is detected. Note that previous data trading protocols need a Trusted Third Party (TTP) or an offline arbitrator to solve disputes, weakening the trust of those protocols. Secondly, the data validity verification process of our protocol is more flexible. Most Importantly, different from all previous designs which only achieve privacy against communication channel eavesdroppers, our protocol achieves privacy against any eavesdropper and the passive arbitrator. The above-distinguishing properties of our protocol are mainly benefited from the homomorphic encryption and double encryption techniques. In addition, our data trading protocol can be instantiated with post-quantum primitives and thus achieves post-quantum security. To demonstrate the feasibility of the proposed protocol, we conduct a comprehensive evaluation with the instantiated cryptographic primitives based on the Ethereum test network.

【Keywords】Protocols; Probabilistic logic; Data privacy; Blockchains; Data integrity; Organizations; Privacy; Data trading; blockchain; fairness; privacy; FHE

【发表时间】2024

【收录时间】2024-10-17

【文献类型】实验仿真

【主题类别】

区块链技术-协同技术-数据管理