ProvNet: Networked bi-directional blockchain for data sharing with verifiable provenance
Data sharing is increasingly popular especially for scientific research and business fields where large volume of datasets need to be used, but it involves data security and privacy concerns. This paper mitigates such concerns by tracking and logging the history of shared data (i.e., provenance reco...
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| Vydané v: | Journal of parallel and distributed computing Ročník 166; s. 32 - 44 |
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| Hlavní autori: | , , , |
| Médium: | Journal Article |
| Jazyk: | English |
| Vydavateľské údaje: |
Elsevier Inc
01.08.2022
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| Predmet: | |
| ISSN: | 0743-7315, 1096-0848 |
| On-line prístup: | Získať plný text |
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| Shrnutí: | Data sharing is increasingly popular especially for scientific research and business fields where large volume of datasets need to be used, but it involves data security and privacy concerns. This paper mitigates such concerns by tracking and logging the history of shared data (i.e., provenance records) while preserving data privacy. This is a challenging problem in the data sharing scenario in this paper because the environment is decentralized and internal logs are not accessible publicly due to privacy concerns. We present ProvNet, a decentralized data sharing platform that can detect malicious users and provide secure provenance records using the newly proposed networked blockchain without disclosing raw data contents. Valid sharing records are collected and stored in the blocknet and misbehavior is detected with the stored provenance records according to our accountable protocols. We give a proof-of-concept implementation, and evaluation results show that the overhead is acceptable.
•A networked blockchain, blocknet, stores data sharing records bi-directionally.•Using MinHash to check datasets' similarities, thus protect data ownership.•Chameleon Hash is leveraged to add future pointers without changing previous hashes.•A provenance graph built from blocknet, provides users' trackability on shared data.•Prototye performance is acceptable, an indexing system designed for optimization. |
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| ISSN: | 0743-7315 1096-0848 |
| DOI: | 10.1016/j.jpdc.2022.04.003 |