Legacy security measures, while offering a baseline level of protection, heavily rely on predefined signatures and a narrow definition of the “abnormal.” They often follow a reactive approach, can be siloed, limiting information sharing, and lack the scalability to handle the terabytes of data generated by today’s complex IT systems.

This is where artificial intelligence steps in.

In this TechRepublic Premium feature, written by Avya Chaudhary, discover more about this crucial cybersecurity matter, get expert views and learn how to protect your business. The download includes advice from Mary Ann Miller, VP evangelist & fraud executive advisor at Prove Identity, and Amit Patel, senior vice president at Consulting Solutions.

Featured text from the download:

An analysis by Bain has revealed a gold rush for generative AI, and it’s all happening at the very beginning of the fight — threat identification. Compared to the other five stages of the SANS incident response model — preparation, containment, eradication, recovery and lessons learned – identification represents the biggest single area of AI adoption.

However, the true power of AI lies in its ability to move beyond mere threat identification to proactive threat hunting. AI tools generate threat detection queries automatically, search through the data and present potential threats without having to inject SQL queries manually.

AI here can also function as a hypothesis augmentation platform, assisting security analysts in refining their guesswork and intuition into structured threat prediction. Now an analyst suspecting lateral movement can use AI to comb through incident logs and network traffic logs for inbound and outbound connections and filter for specific protocols associated with lateral movement without having to write specific queries targeting Server Message Block or attempts to establish remote desktop connections.

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TIME SAVED: Crafting this content required 22 hours of dedicated writing, editing, research and design.