TY - JOUR
T1 - Towards situational aware cyber-physical systems: A security-enhancing use case of blockchain-based digital twins
AU - Suhail, Sabah
AU - Svetinovic, Davor
AU - Rehman Malik, Saif Ur
AU - Jurdak, Raja
AU - Hussain, Rasheed
AU - Matulevicius, Raimundas
PY - 2022
Y1 - 2022
N2 - The complexity of cyberattacks in Cyber-Physical Systems (CPSs) calls for a mechanism that can evaluate critical infrastructures’ operational behaviour and security without affecting the operation of live systems. In this regard, Digital Twins (DTs) provide actionable insights through monitoring, simulating, predicting, and optimizing the state of CPSs. Through the use cases, including system testing and training, detecting system misconfigurations, and security testing, DTs strengthen the security of CPSs throughout the product lifecycle. However, such benefits of DTs depend on an assumption about data integrity and security. Data trustworthiness becomes more critical while integrating multiple components among different DTs owned by various stakeholders to provide an aggregated view of the complex physical system. This article envisions a blockchain-based DT framework as Trusted Twins for Securing Cyber-Physical Systems (TTS-CPS). With the automotive industry as a CPS use case, we demonstrate the viability of the TTS-CPS framework through a proof of concept. To utilize reliable system specification data for building the process knowledge of DTs, we ensure the trustworthiness of data-generating sources through Integrity Checking Mechanisms (ICMs). Additionally, Safety and Security (S&S) rules evaluated during simulation are stored and retrieved from the blockchain, thereby establishing more understanding and confidence in the decisions made by the underlying systems. Finally, we perform formal verification of the TTS-CPS.
AB - The complexity of cyberattacks in Cyber-Physical Systems (CPSs) calls for a mechanism that can evaluate critical infrastructures’ operational behaviour and security without affecting the operation of live systems. In this regard, Digital Twins (DTs) provide actionable insights through monitoring, simulating, predicting, and optimizing the state of CPSs. Through the use cases, including system testing and training, detecting system misconfigurations, and security testing, DTs strengthen the security of CPSs throughout the product lifecycle. However, such benefits of DTs depend on an assumption about data integrity and security. Data trustworthiness becomes more critical while integrating multiple components among different DTs owned by various stakeholders to provide an aggregated view of the complex physical system. This article envisions a blockchain-based DT framework as Trusted Twins for Securing Cyber-Physical Systems (TTS-CPS). With the automotive industry as a CPS use case, we demonstrate the viability of the TTS-CPS framework through a proof of concept. To utilize reliable system specification data for building the process knowledge of DTs, we ensure the trustworthiness of data-generating sources through Integrity Checking Mechanisms (ICMs). Additionally, Safety and Security (S&S) rules evaluated during simulation are stored and retrieved from the blockchain, thereby establishing more understanding and confidence in the decisions made by the underlying systems. Finally, we perform formal verification of the TTS-CPS.
U2 - 10.1016/j.compind.2022.103699
DO - 10.1016/j.compind.2022.103699
M3 - Journal article
SN - 0166-3615
VL - 141
SP - 103699
JO - Computers in Industry
JF - Computers in Industry
ER -