Any organization planning to use IoT should consider digital twins an essential technology, as they provide a bridge between the physical and digital worlds. In fact, everything points to a digital twin technology explosion. Research firm Gartner named the IoT digital twin in its top 10 strategic technology trends for the last two years, estimating that within three to five years, billions of things will be represented by digital twins.
What is digital twin technology? Simply put, it’s the virtual representation of a physical asset — a virtual doppelganger of a thing that can help improve understanding, development and product lifecycle management.
The history of the digital twin dates back to when NASA first started creating mirrored systems in the early days of space exploration that allowed engineers and astronauts to successfully work out how they could rescue the stricken Apollo 13 mission.
Today, IoT digital twins are created to test and build all types of equipment in a virtual environment. Developers can run simulations and tests based on the data collected from physical, real-world IoT sensors, as well as model and monitor devices using artificial intelligence, machine learning and predictive analytics. Digital twins also reduce the security risks associated with IoT devices, as data and applications don’t have to reside on the physical device, only in the cloud. For example, there’s no need to deploy an expensive telematics unit to track a driver’s behavior as the application can simply run in the cloud.
Like everything in the world of IoT, data is the primary driver of the IoT digital twin, and it’s the most valuable output of one. As much of this data is sent to cloud-based systems for processing and analysis, IoT data security needs to be a top priority when deploying IoT and digital twins.
History, however, has shown that security is often overlooked in new, fast-moving technologies, leading to valuable and sensitive data being lost and stolen. In the rush to take advantage of digital twin technology, it’s important that enterprises take the time to secure data generated by IoT sensors and then stored and processed in the cloud — just like any other data.
While IoT data is less likely than many cloud application data to contain personally identifiable information, it is still highly probable that it will be data hackers will be willing to spend time and money trying to steal it. It is essential to ensure that only authenticated processes and users with the correct permissions can access IoT digital twin data.
Roles should be created that manage access to specific digital twin resources and actions following the principle of least privilege to limit the role of each device, sensor and person. Data also needs to be encrypted while at rest and only transmitted over secure protocols.
Both Microsoft Azure IoT and Device Shadow Service for AWS IoT provide security and identity tools to help manage access and authentication for IoT digital twins, as well as to facilitate tasks such as refreshing authentication credentials and keys on a regular basis. Those involved in IoT projects should be familiar with the security tools available and how best to use them.
There’s no doubt the IoT digital twin can transform products and services, as well as reduce development costs and operating and capital expenses. However, some of the cost savings and profits they generate have to be put back into ensuring they are properly secured. If they’re not, then organizations will experience data breaches and attacks that can compromise proprietary technologies and affect critical infrastructure assets and services.