A Digital Twin is a computer-based program that uses real-world data to create a simulation and predict how a product will work. Advancements in machine learning and factors such as big data have made these virtual models an integral part of modern technology to drive innovation and improve performance. The global digital twin market in 2021 was $6.5 billion and is predicted to reach $125.7 billion by 2030, with a CAGR of 39.48% in 2021-2030.
Digital twins reflect a real-world system, allowing designers and engineers to examine in great clarity how different conditions will affect it, such as how a wind turbine will function in a hurricane. However, besides manufacturing and business opportunities, professionals can use the technology to analyze security controls’ security problems and capabilities in computing environments.
The Security Risk of Digital Twin
There are four areas of major concern:
- System Access: If someone has access to your digital twin, they may be able to take control of the physical assets and replicate it. More dangerously, they can gather knowledge about the system or asset. Uncontrollable behaviors may result from this.
- IP Theft: If your digital twin is a blueprint for intellectual property, hackers may be able to reverse engineer and recreate that property, avoiding the need for their research and development. There is currently a substantial market for this type of hacking activity.
- Non-Compliance: Stricter privacy regulations, such as Europe’s recently implemented GDPR, have increased pressure on organizations to ensure data compliance. If your digital twin compromises this, it could result in significant financial and reputational damage.
- Information Integrity: When people have access to data, they can make unauthorized changes, and information can lose its integrity. To ensure the integrity of information, it is necessary to collect the correct information, interpret it correctly, and have authentication and security measures in place to prevent unauthorized changes.
All systems should be designed to be secure. If the digital twin is not designed to be secure, it may become a variable of attack.
Changing the perceived behavior of the digital twin or physical object by intercepting and modifying data is a well-known attack strategy in critical infrastructure and is common in any operational technology. Such manipulations may cause the human operator or the resulting analytics to base their decisions on incorrectly masked data. If a digital twin is intended to provide direct feedback or control operational systems, it may directly impact those systems if not properly secured.
Nonetheless, developers of digital twin technology see its value as a cybersecurity tool. Security teams can already use digital twin technology to test not only larger environments but also to become more specific and test more focused systems and infrastructure.
A nested digital twin environment can be created to uncover specific details about risk, vulnerabilities, and training and optimize operations.
An Emerging Technology
Although digital twin technology has applications in very large environments, such as power grid protection, network protection, and manufacturing, it emphasizes the technology’s challenges.
Although there is some indication that digital twins are workable in small-scale systems, they have not been demonstrated to scale to our knowledge.
Numerous factors influence how fully cyber-physical, complex business processes and supply chains will be implemented in a digitally connected environment. Digital twins are a new concept that is rapidly evolving.
Digital twins are not ready for mass adoption, especially regarding cyber resilience challenges. Today’s often-imperfect data and insight into the physical system, combined with cost constraints, results in puddled realities.
A database containing sensitive information is referred to as a digital twin. It is just as important to protect the digital twin as it is to protect the system it analyses.
Security professionals will use the technology to assess vulnerabilities and system capabilities, but they must keep a close eye out for possible risks.