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Digital identities are also evolving at pace and identity security is now a crucial aspect of cybersecurity .

As we continue to digitally transform organisations , so the importance of secure and reliable digital identities has grown .

A multitude of innovations and trends are being ushered into this area , ranging from advanced biometrics to the integration of artificial intelligence and machine learning to meet the changing needs of businesses , individuals and governments .

The growing use of synthetic identities combined with deepfakes

There are growing concerns related to identity fraud , insider incidents , the need for tighter data security controls , while not impacting the user experience .

There has been a growing number of incidents of cybercriminals using synthetic identities combined with deepfake content , whereby they create synthetic identities in several ways , such as by combining stolen personal information from several people into a new identity , thereby inventing a new identity that ’ s completely fictitious and doesn ’ t rely on real personal data .

They then use these identities in ways that allow them to build a shallow history that they can use for identity checks with major banks and retailers .

To counter this tactic , biometrics such as facial recognition , fingerprint scanning and voice recognition are becoming increasingly popular as a means of identity verification . These are more secure than traditional passwords and can help prevent identity theft .

Despite these attempts to counter identity theft , however , the threat remains large and growing .

This makes it even more important for businesses to be informed around identity security and how they can secure their organisations , employees and customers .

Employees , in particular , must be monitored with the right policies and tools , as insider incidents are also growing , and over-privileged access and passive data security tools that only monitor traffic leave critical data vulnerable to exfiltration .

All of these factors are fuelling demand . According to Global Insights , the global Identity and Access Management ( IAM ) market is expected to grow at a compound annual growth rate of 12.6 % from 2023 to 2030 to reach $ 41.52 billion by 2030 .

Demand for more advanced biometric verification

While fingerprint and facial recognition technologies have already made their mark , emerging ID trends indicate a shift towards advanced biometric verification methods .

The integration of AI and machine learning ( ML ) is revolutionising identity verification . AI-powered systems equipped with pattern recognition capabilities can identify anomalies and detect fraudulent attempts in real time . These systems analyse patterns and behaviours to identify outliers

As we continue to digitally transform organisations , so the importance of secure and reliable digital identities has grown .

and inconsistencies , adding an invaluable layer of security to the verification process .

Machine learning algorithms act as adaptive detectives , continuously evolving to recognise and respond to new identity fraud tactics , enhancing the overall accuracy of the verification process .

Cybercrime-as-a-Service ( CaaS ) allows criminals to purchase or rent tools and services that enable them to carry out identity-based attacks without having to develop the expertise themselves , meaning more criminals are capable of such attacks .

Additionally , liveness checks are becoming more frequent in biometric verification , adding an extra layer of security by ensuring the genuine presence of the individual undergoing verification . Liveness checks require users to perform real-time actions , such

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