Identity Remains the Primary Target for AI-Driven Cybersecurity Attacks

As is well known, biometric information of natural persons, such as facial features and voice, are highly distinctive and strongly linked to identity attributes. What happens if this information is "lost"? With the continuous advancement of Artificial Intelligence technology, the use of AI for deepfake techniques—such as face and voice swapping—for scams, defamation, and extortion has become increasingly widespread. Particularly with the rise of generative AI, hackers are frequently using it as their "attack weapon" to launch complex and automated cyberattacks.

According to reports, AI-based deepfake fraud surged by 3000% in 2023, AI-driven phishing emails increased by 1000%, and password attack attempts reached up to 30 billion per month.

These AI security incidents and attack statistics highlight that identity remains the primary target for attacks. Recent findings from IBM's 2024 X-Force Threat Intelligence Index further reinforce this view, showing a 71% increase in cyberattacks exploiting identity information in 2023.

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How to Address AI Security Crises from an "Identity" Perspective?

From a cybersecurity standpoint, AI amplifies existing threats—such as phishing emails, malware, and social engineering—and introduces new threats like AI-driven automated attacks and deepfakes.

Given the series of security crises brought about by AI and the fact that identity remains the primary target for attacks, Paraview recommends that organizations continuously strengthen their digital identity security and rebuild digital trust to more effectively address AI-related security challenges.

Adopting the "Identity-first" Zero Trust cybersecurity framework is currently the best approach for enhancing digital identity security. In a Zero Trust architecture, the IAM system defaults to considering all entities—both human and non-human—within the enterprise’s digital environment as untrusted.

Entities must undergo real-time, context-based dynamic authentication and analysis, and must meet risk-based, fine-grained access control policies and authorization mechanisms before they can access specific resources. This ensures that only the correct entities can access the right resources at the right time and under the right conditions. This approach not only reduces the attack surface and lowers the risk of identity and credential theft but also improves the overall user experience.

Conclusion

The above discussion addresses how to respond to AI security crises from the perspective of identity security. Of course, this is far from exhaustive, but it remains an essential foundation for organizational security. 

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