DT Cyber is a joint project between Technological University of the Shannon and Queen’s University Belfast.
PIs: Dr.Brian Lee (TUS)
Digital Twins(DTs) are a virtualised version of a system, used to run simulations, study performance, develop insights, and generate possible improvements. Meanwhile, the field of cyber-security continues to pose immense societal and technological challenges to protect data and infrastructure against disruptive and destructive attacks. Nevertheless, emerging DT technologies and workflows present opportunities to enable significantly improved cyber-attack monitoring and response solutions. This is especially true for cyber-physical systems (CPS, merging of information systems and industrial control systems generates). It is recognised that the resilience and dependability of modern CPS is inextricably linked to their security in both cyber and/or physical aspects. Therefore, approaches that co-simulate cyber and physical attributes of CPS can offer a significant advancement beyond traditional cyber-only techniques.
DT-based solutions offer a promising framework to support improved system monitoring and attack response, by delivering insights and countermeasures in real time to detect and respond to evolving cyber threats against CPS. The majority of research that addresses DTs and cyber security tends to focus on the problem of providing cyber security for DTs, i.e. protecting the data or intellectual property associated with a CPS, which a DT will create or consume. On the other hand, the use of DTs to enable cyber security has seen some initial research but is less advanced.
The main goal of the project is to figure out how DT will be used to help build a resilient CPS with follow questions:
➛ Investigating Social IoT Trust Models
To answer these questions, we will conduct a fundamental research study to address questions 1 and 2. To answer question 3, we propose a novelmethod for analysing CPS architectures to identify which subsystems should be included in a DT platform. We will build on related and widely cited work, which provides a general framework for the modelling of DTs, using three phases: machine modelling, modelling virtual sensors, and definition of updatable parameters. While this provides a good foundation for our proposed research, it lacks consideration for cyber-physical security attributes that we propose to explore. In previous work we investigated a STRIDE method for threat analysis in CPS. This approach uses the Data Flow Diagram (DFD) technique to identify cyber-security “trust boundaries” in a CPS (Fig. 1). We propose that a modified DFD approach can be used to identify and draw DT boundaries around subsystems that should be included in DTs to provide cyber-security monitoring and response.
We will carry out a case study to demonstrate and evaluate the use of the DT-Cyber DT-DFD methodology on two case studies.
Industrial Multi Robot System (MRS): This task will develop a comprehensive industrial MRS scenario. It will feature the use of the Robot Operating System (ROS) to enable a distributed and heterogeneous set of robots and will be mapped to industrial networking reference models such as the Purdue model.
Energy Case Study: A second scenario will study the control of renewable energy resources on the electrical grid, such as wind, which is a vital strategic energy source on the island. Integration with ICT platforms and control via the electrical distribution network presents a significant cyber-attack surface for critical national infrastructure, and will be modelled in this task.
Institutional level: DTCyber aligns with the TUS research area of cyber security and robotics and the combination of both in the smart polymer manufacturing subtopic of the circular economy. At QUB, the project aligns with the strategic aims of the Centre for Secure Information Technologies (CSIT), where cyber-physical and industrial control systems are a core thematic area.
National level: DTCyber is aligned with the Irish government research area Data Analytics, Management, Security, Privacy, Robotics and Artificial Intelligence. In Northern Ireland, as the UK’s Innovation and Knowledge Centre for Cyber Security Technologies, CSIT plays a key role in supporting the NI Executive’s Economic Recovery Action Plan and the New Decade, New Approach deal which set a goal of achieving 5,000 cyber security jobs by 2030.
More details coming soon
Technological University of the Shannon,Athlone Campus,University Road, Athlone,Co. Westmeath.
T: 353 (090) 6468000E: firstname.lastname@example.org
Connect with Us