块链
可验证秘密共享
计算机科学
代理(统计)
代理重新加密
计算机安全
加密
计算机网络
公钥密码术
机器学习
集合(抽象数据类型)
程序设计语言
作者
Yangyang Long,Changgen Peng,Yuling Chen,Weijie Tan,Jing Sun
标识
DOI:10.1109/jiot.2024.3449412
摘要
Fair data trading is a complex process that is often hindered by a fundamental issue of trust between data suppliers and collectors. This mistrust can lead to an impasse: data collectors hesitate to pay upfront without the data in hand, while data suppliers hold back the data until they are assured of payment. Though enlisting a trusted third party may mitigate these issues, it also presents distinct security challenges that must be carefully considered. Observing that the blockchain technique has great potential to improve security, efficiency, and transparency of data trading, we present a blockchain-based fair data trading scheme, called BFFDT, which allows the data seller trade its data in part with an interested purchaser through a smart contract for revenue. In BFFDT, the data publisher first generates the authenticated tags based on the data fields and corresponding attribute values, then encrypts the corresponding attribute values individually and generates a dynamic Merkle hash tree (D-MHT) to ensure the consistency of the attributes and attribute values. In addition, we design an innovative pairing-based proxy re-encryption mechanism to transmit the ciphertext of a symmetric key to the purchaser’s public key via a re-encryption key without any third-party intermediary, and verifies the re-encryption key using the verifiable commitment. Furthermore, the BFFDT is formally proven to be secure against the deceitful actions of both the fraudulent seller and buyer, and the experimental outcomes further confirm that BFFDT offers high efficiency and practical applicability.
科研通智能强力驱动
Strongly Powered by AbleSci AI