A comprehensive survey of digital twins: Applications, technologies and security challenges

Abstract

Alongside advancements in Artificial Intelligence (AI), significant progress has been made in big data processing, edge/cloud computing, and ubiquitous computing in the past two decades. These advancements catalyzed the development and adoption of Digital Twins (DT) across various domains, serving as virtual replicas of Physical Objects (POs). DTs provide advanced visualization and simulation capabilities, enabling effective estimation, optimization, and forecasting of PO's behaviors. However, the widespread adoption of DTs has introduced various security threats, vulnerabilities, and attacks. Despite ongoing research in DT applications and security, there is a lack of systematic review of the DT security literature across domains and architectural layers. This study fills this gap by systematically reviewing DT research, focusing on three interrelated aspects: DT applications, architectural layers, and security. We explore DT's architectural layers, functional requirements, application, and creation software to identify potential threats, attacks, and vulnerabilities specific to DT layers and application domains. We then systematize our findings under a unified security framework and pinpoint countermeasures against identified security challenges. Furthermore, our study explores DT's role in mitigating existing cyber threats, and we conclude our work by identifying open challenges and potential research directions.