  The potential of digital twin technology is yet to be fully realized due to
its diversity and untapped potential. Digital twins enable systems' analysis,
design, optimization, 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 digitization, 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.
