A Distributed Ledger Approach to Digital Twin Secure Data Sharing

Abstract

The Digital Twin refers to a digital representation of any real-world counterpart allowing its management (from simple monitoring to autonomy). At the core of the concept lies the inclusion of the entire asset lifecycle. To enable all lifecycle parties to partake, the Digital Twin should provide a sharable data base. Thereby, integrity and confidentiality issues are pressing, turning security into a major requirement. However, given that the Digital Twin paradigm is still at an early stage, most works do not consider security yet. Distributed ledgers provide a novel technology for multi-party data sharing that emphasizes security features such as integrity. For this reason, we examine the applicability of distributed ledgers to secure Digital Twin data sharing. We contribute to current literature by identifying requirements for Digital Twin data sharing in order to overcome current infrastructural challenges. We furthermore propose a framework for secure Digital Twin data sharing based on Distributed Ledger Technology. A conclusive use case demonstrates requirements fulfillment and is followed by a critical discussion proposing avenues for future work.

Blockchain-Empowered Digital Twins Collaboration: Smart Transportation Use Case

“…In [12], the authors have used DLT to develop a protocol to guarantee the transfer of values between DTs in economic systems. Furthermore, a framework for secure DT data sharing based on DLT is proposed to track events and provenance information along with an asset's lifecycle and increase transparency for all participants [41].…”

“…Figure 5 describes the ledger-based DT model. At the technical level, the ledger-based DT model needs to define the five components [10,41]: (1) registered DT owner, (2) DT status, (3) timestamp, (4) transaction, and (5) ledger database. The information that maintains a physical object's specifications is stored within the ledger, such as the DT owner.…”

A Flexible Security Analytics Service for the Industrial IoT

“…According to IIRA or RAMI 4.0, we instantiate an architecture based on a middleware, which yields machines and their edge nodes in an Industrial Control System (ICS) and a cloud to process and analyze the gathered data. Therefore, we derive the following entities that are involved within the architecture, i.e., life cycle parties of machines [7] and Cloud Computing entities: CSP, CSC, network service provider (NSP), internal IT department, manufacturer, distributor, owner, and maintainer.…”

A Knowledge-Based Digital Lifecycle-Oriented Asset Optimisation

“…The application areas of a DT range from the use in i) product design [13] specifically in simulation [14], to ii) production, iii) maintenance [9] and iv) networking and communication across asset manufactures and operators [15]. The DT used in simulating production applications often includes data of the asset operators, material, equipment, tools, environment, behaviour, rules and dynamic models, derived from expert knowledge, which can be optimised by the DT [14].…”

“…The combination of these different data sources becomes even more important when a DT is used across the ALC phases. In this case, data exchange between asset manufacturer and operator is a necessity [15].…”