How to Improve Cybersecurity With Digital Twins

Digital twins are highly accurate virtual versions of real-life places or things. They have become widespread in industries such as manufacturing because decision-makers want to test factory layouts, product prototypes or other specifics before approving them.

Some leaders also build digital twins of critical equipment to detect when a machine’s operating conditions deviate too much from the virtual version’s norms, indicating an urgent problem to investigate. How can cybersecurity practitioners apply digital twins to their defensive strategies?

Choose the Digital Twin’s Scope

Digital twins are more involved than some people realize. Those interested in using them will get the best results by understanding what proposed digital twins will help them monitor. Digital twins have a three-layer architecture with edge servers, analytics software, and more. More specifically, there are hardware, software, and middleware elements.

The hardware layer includes elements such as IoT sensors and routers, while the middleware components span connectivity, data processing and other essential functions. Finally, the software layer could feature machine learning modules, data dashboards or simulation tools, among others.

Digital twins are highly customizable and will have various functionalities according to an organization’s or client’s needs. An early step in creating the digital twin must involve determining its scope. Will the digital twin represent an entire corporate network or specific, highly critical internet-connected devices? Answering that question allows people to assess related necessities about how the digital twin will work and its role in strengthening cybersecurity.

Apply the Digital Twin to Threat Intelligence

New and emerging cyberthreats keep internet security practitioners proactive, consistently trying to stay ahead of the bad actors. That can be a challenging aim, but digital twins can make it easier.

One example comes from a company that has spent a decade capturing threat details. People from that enterprise gather information from technical sources, the internet, and the dark web, using it to help cybersecurity professionals recognize and prepare for the attacks that could compromise their networks.

Part of the digital twin includes information about topics that have recently caught people’s attention and dominated their online conversations. Executives hope the insights will improve cybersecurity practitioners’ workflows, allowing them to work faster and more effectively. Additionally, users can become aware of potential threats faster, allowing them to respond to and mitigate them more quickly than they could without the digital twin.

Digital twins are versatile, allowing people to update them as conditions change. Analysts believe their market worth will reach $154 billion by 2030. The ability to apply them to various situations is one reason for the anticipated continuation of these tools’ already widespread popularity. As the cybersecurity landscape evolves, digital twins can respond similarly by reflecting the latest threats in their stored data.

Use the Digital Twin for Anomaly Detection

Spotting potential network intrusion attempts is not easy, but digital twins can supplement human efforts. One possibility is to build a digital twin to reflect normal, expected network activity. Then, set it up to flag anything that strays from such conditions.

Financial institutions take a similar approach by gathering data on individual customers and automatically blocking transactions that are too far outside of how, when, why, and where those people spend. Such applications explain why someone may need to contact a credit card provider before purchasing a big-ticket item that is out of character for them.

There are three types of anomalies to detect as cybersecurity practitioners. The first is a point anomaly, which is a single unexpected event. Then, there are collective anomalies, which only stand out as abnormal when viewed in a group, when people may spot unusual patterns.

Finally, contextual anomalies are unexpected events that appear out of context relative to the baseline. Suppose a cybersecurity team learns a site’s traffic is lowest in the early morning. If activity suddenly spiked during that time, they would know to investigate the cause.

People can build digital twins to support their anomaly detection efforts, increasing their chances of knowing about unusual events sooner. Quick action reduces the chances of infiltrators entering networks unnoticed and wreaking havoc for days or weeks before someone discovers them.

Select Appropriate Goals

What do people want to achieve by building a digital twin for cybersecurity? They must determine that to keep projects on track for completion and make the outcomes as impactful as possible. One example comes from a project where people will build a digital twin of an electric grid.

Those involved will use it to mitigate cascading failures and create proactive defense mechanisms. Additionally, they believe the digital twin will improve cybersecurity by boosting resilience and facilitating faster recoveries from outages.

Decision-makers often use digital twins to run various scenarios in controlled, virtual environments. Seeing the ripple effects of those events allows users to consider how they would respond if the scenarios occurred in real life.

The electric grid’s digital twin will predict potential threats, improving preparedness. Additionally, this four-year project will allow participants to test new applications that could expand digital twin utilization for power companies and other industries. Cybersecurity experts warn that critical infrastructure operators are prime targets for cybercriminals since such attackers want to cause the most significant disruptions for the largest number of people.

Identify the Biggest Risks With the Digital Twin

Cybersecurity professionals frequently use frameworks that detail best practices and reveal whether the respective organizations are doing the right things or need to improve. However, learning about the most prominent risks affecting particular industries and building digital twins to reduce them are also good strategies.

Such was the case when an agency within the United States Department of Defense contracted a service provider to build a proof-of-concept digital twin to reduce cyberattacks on a small manufacturing system. The tool will rely on synthetic data about potential cyberattack vectors, enabling users to identify and defend against infiltrations before they affect the organization’s operational technology.

The project’s participants believe their work will improve awareness and protection measures, making it harder for attackers to target the organization successfully. Since cybersecurity risks can vary depending on factors such as an entity’s industry, resources and size, people should strongly consider creating digital twins that can help them prepare for known threats and unfamiliar challenges that could arise soon.

People can consider adopting this approach by using digital twins to learn which issues would cause the most damage if not addressed in time. Then, they can adjust their cybersecurity measures to increase organizational readiness for those potentially disruptive problems, reducing the likelihood of them causing problems in real life.

Digital Twins Are Worth Exploring

These examples and tips should inspire people interested in applying digital twins for tighter cybersecurity. In addition to following the suggestions here, individuals should consider how other industry peers use these tools for better cyberattack protection.