A Review of Digital Twins and Their Application in Cybersecurity Based on Artificial Intelligence

Abstract

The potential of digital twin technology is yet to be fully realised due to its diversity and untapped potential. Digital twins enable systems’ analysis, design, optimisation, and evolution to be performed digitally or in conjunction with a cyber-physical approach to improve speed, accuracy, and efficiency over traditional engineering methods. Industry 4.0, factories of the future, and digital twins continue to benefit from the technology and provide enhanced efficiency within existing systems. Due to the lack of information and security standards associated with the transition to cyber digitisation, cybercriminals have been able to take advantage of the situation. Access to a digital twin of a product or service is equivalent to threatening the entire collection. There is a robust interaction between digital twins and artificial intelligence tools, which leads to strong interaction between these technologies, so it can be used to improve the cybersecurity of these digital platforms based on their integration with these technologies. This study aims to investigate the role of artificial intelligence in providing cybersecurity for digital twin versions of various industries, as well as the risks associated with these versions. In addition, this research serves as a road map for researchers and others interested in cybersecurity and digital security.

A secure framework for IoT‐based healthcare using blockchain and IPFS

“…Many experts in the field, including authors, researchers, and scientists, have published literature reviews and survey papers on the topic, 36–41 highlighting the numerous challenges, potential solutions, frameworks, opportunities, and research directions for enhancing the security and overall effectiveness of healthcare systems. Upon reviewing recent literature in the field of IoT‐based healthcare, it becomes evident that certain challenges and gaps persist, demanding innovative solutions., which not only pose a risk of single‐point failure but also hinder scalability and robustness.…”