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Blockchain-based verifiable privacy-preserving data classification protocol for medical data.
- Source :
-
Computer Standards & Interfaces . Aug2022, Vol. 82, pN.PAG-N.PAG. 1p. - Publication Year :
- 2022
-
Abstract
- • We propose a blockchain-based Verifiable privacy-preserving Data Classification protocol (VeriDC) for medical data. • We define the system model of the verifiable privacy-preserving data classification protocol in blockchain setting and formalize its security model. • We propose a concrete VeriDC protocol by using verifiable OPRF. We prove the security of VeriDC protocol in the random oracle model and compare VeriDC with the related scheme to evaluate the effectiveness of VeriDC. 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. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 09205489
- Volume :
- 82
- Database :
- Academic Search Index
- Journal :
- Computer Standards & Interfaces
- Publication Type :
- Academic Journal
- Accession number :
- 156362033
- Full Text :
- https://doi.org/10.1016/j.csi.2021.103605