AI and ML: The Keys to Better Security Outcomes

December 6, 2023

From reducing complexity in the architecture to supercharging risk posture, building cyber resilience should be top-of-mind for every organization. But what does it take to achieve true cyber resilience in today’s rapidly changing cybersecurity landscape? How do you stay ahead of the latest threats while defending against zero-day attacks?

I had the pleasure of speaking with Anand Oswal, senior vice president and general manager of network security at Palo Alto Networks. He shared his thoughts on the direction of enterprise security and how organizations can prepare for what’s next.

Three Major Trends in Cybersecurity

The Role of Data in AI

Our discussion goes deeper into the impacts of AI and ML on cybersecurity. Oswal emphasizes how traditional approaches to cybersecurity can’t keep up with today’s threats.

Take URL filtering as an example, where policies were created based on URLs labeled and stored in a database. Today, malicious actors can easily activate and deactivate URLs, making databases obsolete before security teams can respond.

He also emphasizes that AI and ML are key to analyzing data and recognizing attack patterns. This requires large amounts of data from across your infrastructure — network, endpoint, cloud and other critical enforcement points. When stitched together, this data provides key insights into your infrastructure, drives attack recognition and enables rapid incident response in the event of a breach.

“You can only have good cybersecurity through AI and ML. It’s almost impossible to do it manually,” says Oswal. “Cybersecurity is the only industry with active adversaries. Those adversaries are using the power of AI and ML, and attacks are getting more and more sophisticated.”

Why Security Consolidation is Key to Better Outcomes

Pulling data from across your entire infrastructure for AI is challenging when your products and services are siloed. They use different datasets, contexts, logging conventions and UIs, hindering AI’s ability to recognize patterns. But with security consolidation, your security products work seamlessly together to share intelligence and defend against sophisticated attacks.

Consolidation is more than using AI to detect threats, as Oswal explains. It also reduces “the overall complexity of your environment.” Today’s organizations on average employ 31.5 security tools — each with its own procurement, implementation and maintenance requirements.

By consolidating your detection tools, you can significantly reduce the resources needed to manage these processes, build strategic relationships with your vendors and achieve better security outcomes.

Securing Your Organization Starts with Consolidation

So, what advice does Oswal have for security leaders in today’s changing cyber environment? It all comes down to the right approach.

“As you look at consolidation, an important factor is: how do you ensure enterprise-wide Zero Trust? How do you get consistent security for users accessing applications and data from any device, on any network, from any location? How do you get consistent best-in-class security? How do you ensure the most optimal user experience? And how do you ensure the best experience for NetSec admins? All of this is only possible when you have a platform-centric approach.”

Security leaders have a tremendous opportunity to rethink their defenses and build an AI-driven risk posture. That starts with choosing a partner that combines best-of-breed security with a platform approach.