Russ Ernst, CTO at Blancco considers the pros and cons of a digital twin.

The concept of a digital doppelganger or digital twin has evolved from the realm of science fiction to practical application in various industries with expected growth of 61% over the next five years. At their core, digital twins are virtual replicas of a location, system, or object, and they give organisations the opportunity to test scenarios prior to changes in the real environment.

As businesses increasingly adopt these virtual counterparts to enhance their operations, understanding their role in managing the information lifecycle and how they reduce risks has become crucial. Yet these twins also come with a host of challenges including more vulnerabilities and data losses. The proactive data management will be invaluable for overcoming threats, non-compliance, and information inaccuracies.

The benefits

Digital twins, commonly used within industries such as telecommunications, healthcare, and utilities, offer organisations a unique opportunity to gain insights and develop their understanding physical environments without impacting the real thing. This enhanced understanding allows organisations to identify potential vulnerabilities and points of exposure throughout the lifecycle, leading to more effective risk mitigation strategies.

One of the key advantages of utilising digital twins lies in their potential to minimise the unnecessary storage of large amounts of data. With an intricate understanding of the information lifecycle, organisations can identify redundant, obsolete, or trivial (ROT) data that may contribute to data bloat.

This proactive data management approach not only streamlines operations, by preventing margin of error, but it also reduces the attack surface. By limiting the volume of potentially sensitive information available and minimising unnecessarily stored data, organisations can significantly lower the chances of exposure and unauthorised access from a threat actor, thus enhancing their cybersecurity posture.

Digital twins can also play a pivotal role in improving the accuracy of an organisation’s data. Through constant synchronisation and feedback loops, discrepancies between the virtual counterpart and the real-world entity can be identified and rectified. This iterative process ensures that the digital doppelganger remains a reliable source of information, contributing to informed decision-making and accurate analytics.

The challenges

However, digital twins do not exist without fault. As they rely on data from various sources, it makes it possible for criminals to target these data sources, or the sources’ connection with the twin, to access sensitive information. This could include customer data, proprietary information, or other confidential data that could be exploited for financial gain.

Attackers may also attempt to disrupt or compromise the twin’s functionality, which can be done with malware and then held to ransom. If successful, this could lead to inaccurate data representation, faulty predictions, and even cascading effects in the physical system.

What’s more, the accuracy of the data produced by the digital twin is solely dependent on the source data being accurate. Any discrepancies with the source data could lead the twin to produce inaccurate results and have knock on effects if not rectified. To fully leverage the benefits of digital doppelgangers and ensure accuracy while mitigating associated risks, organisations must adopt a structured approach to data disposal. This includes a few critical steps:

Data classification: Organisations must define what data they have, its kind, value, location, usage, access, and retention periods in order to properly manage it. For risk management, legal discovery, and other circumstances, proper data classification and minimisation are crucial. The good news is that 91% of surveyed organisations understand data classification is an important first step for achieving data security. Yet worrying only 36% stated they were beginning to implement a policy around it.

Retention policies: It’s important to establish clear retention policies that determine how long specific types of data should be kept before being erased. This helps prevent data from accumulating unnecessarily. As more organisations move to the cloud, having clear data policies reduces risk, especially considering 65% of organisations in industries like healthcare and financial services claim switching to cloud increased the volume of redundant, obsolete, or trivial (ROT) data they collect.

Regular audits: When sanitising information, an audit trail is essential to maintain accountability—it confirms that data has been entirely deleted for compliance purposes, offers liability defence in the event of a breach, establishes that the chain of custody has been kept, and more. Maintain detailed records of data disposal activities to demonstrate compliance with regulatory frameworks. All data erasure, whether on-premises or in the cloud, should be verifiable and able to be traced back to when it was deleted. Dispose of data that no longer serves a purpose and adhere to legal requirements.

Secure disposal methods: Virtual storage is never infinite, but it’s also crucial teams make sure they utilise secure methods of data disposal, such as encryption or shredding, to ensure data cannot be easily recovered by unauthorised parties. Lingering data can pose a data breach and liability risk, by just simply being available for exploit by threat actors.

By effectively implementing these steps, organisations can maximise the benefits of their digital twins while minimising vulnerabilities. These virtual counterparts can therefore become the valuable assets in enhancing data accuracy, optimising operations, and strengthening cybersecurity measures they were designed to be.

The key lies in utilising the insights gained from the digital doppelganger’s understanding of the information lifecycle to drive informed decision-making and secure data management practices.

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