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

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.

Distributed Ledger for Cybersecurity: Issues and Challenges in Railways

“…There is a need for a broader prospective with governance from a technology-driven to a need-driven approach with changes in technology and administrative processes to bring information integrity [49]. In railways, blockchain has been tried in different scenarios such as ticketing with data access and competition preservation, transit, and customs, operations system monitoring, control, and maintenance [14,17,[50][51][52]. Ongoing developments to fulfil business requirements through an advancement in technology, improving understanding, and support for the implementation of such requirements has come through many ongoing projects [53][54][55][56][57][58].…”

“…Further, it is of interest to share the data with data processing experts to facilitate improved data analytics and the generated information with the correct stakeholders. The data collected over a period even from a single route may have different ownership and many interested parties [17].…”

Creating a Traceable Product Story in Manufacturing Supply Chains Using IPFS

“…Researchers interested in supply chain traceability have carefully examined blockchain attributes like durability, transparency, immutability, decentralization, and verifiability in various industry contexts [2]- [6]. To realize the benefits of these attributes, efforts have been made to promote a shared understanding of data using vocabularies [3] and ontologies [7], durably tag objects and secure reliable data inputs [8], safeguard confidentiality [3], [4], [9], [10], and create digital representations of assets and liabilities in manufacturing supply chains. Particularly relevant for this paper is the work on digital representations of manufacturing chains where raw materials and goods are transformed [6], [9] and where ag-978-1-7281-8326-8/20/$31.00 ©2020 European Union gregation, mixing, and disaggregation is common [5].…”