@matthiaslohr

Ensuring Genuineness for Selectively Disclosed Confidential Data using Distributed Ledgers: Applications to Rail Wayside Monitoring

, , , and . 2nd IEEE International Conference on Blockchain, page 477-482. IEEE, (2019)

Abstract

In railway incidents, data from sensors installed on railway tracks can help finding the cause of the incident and identifying the responsible parties. Since the data collected may contain business-relevant information, it is usually treated as confidential by the companies collecting it. However, this data can only be considered as evidence if it can be proven that the data is genuine and unaltered, even if it is only accessible for involved companies in the first place. In this paper, we present an approach to ensure the genuineness of confidential railway measurement data using distributed ledgers and describe an approach for selectively sharing parts of the data without compromising confidentiality or the verifiability of genuineness. We also discuss how our approach can be generalized beyond the railway domain to show how distributed ledger-based approaches can be used to ensure the genuineness of confidential and selectively shared data.

Links and resources

DOI:
10.1109/Blockchain.2019.00072
BibTeX key:
Lohr2019DataGenuineness
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