Blockchain-based verifiable privacy-preserving data classification protocol for medical data

【Author】 Zheng, Xiaokun; Zhao, Yanqi; Li, Huilin; Chen, Ruonan; Zheng, Dong

【Source】COMPUTER STANDARDS & INTERFACES

【影响因子】3.721

【Abstract】Massive IoT devices are used for data collection with the fast development of the Internet-of-things (IoT). For example, wearable devices are used to collect users' health data and conduct health monitoring. However, many private information are involved in medical data. Privacy-preserving data classification scheme (PPDC) provided an effective approach to balance the utility and the privacy of data. In the PPDC schemes, a fully trusted auditor is employed to validate the result of data classification. To reduce trust on the auditor, we provide a simplified version of the PPDC scheme. We propose blockchain-based verifiable privacy-preserving data classification protocol (VeriDC) for medical data. It makes the data center check the classification result without involving an auditor. We provide the system model of the verifiable privacy-preserving data classification protocol in blockchain setting and formalize its security model. By using verifiable oblivious pseudorandom function(verifiable OPRF), we can generate a verifiable proof and post it on blockchain to guarantee the transparency of data classification. We present a concrete construction and prove its security. Finally, we compare VeriDC with the related schemes to evaluate the effectiveness of VeriDC.

【Keywords】Blockchain; Data classification; Verifiable OPRF; Medical data; Privacy protection

【发表时间】2022 AUG

【收录时间】2022-01-12

【文献类型】期刊

【主题类别】

区块链技术--