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Machine learning in Palo Alto firewalls adds new protection for IoT, containers

Palo Alto Networks has released next-generation firewall (NGFW) software that integrates machine learning to help protect enterprise traffic to and from hybrid clouds, IoT devices and the growing numbers of remote workers.

The machine learning is built into the latest version of Palo Alto’s firewall operating system – PAN 10.0 –  to prevent real-time signatureless attacks and to quickly identify new devices – in particular  IoT products – with behavior-based identification.

NGFWs include traditional firewall protections like stateful packet inspection but add advanced security judgments based on application, user and content.

“Security attacks are continually morphing at rapid pace and traditional signature-based security approaches cannot keep up with the millions of new devices, running a variety of operating systems and software stacks coming on the network,” said Anand Oswal senior vice president and GM at Palo Alto. “IoT devices, which are growing exponentially, exacerbated that issue because they have so many of their own different agents, patches and OS’s it’s impossible to set security policies around them.”

Oswal said the ML in its new NGFW uses inline machine-learning models to identify variants of known attacks as well as many unknown cyberthreats  to prevent up to 95% of zero-day malware in real time. As it collects telemetry information from the network and combines it with existing Palo Alto data, the firewall can learn behaviors, recognize trends and recommend appropriate security policies, Oswal said.

In addition, PAN 10.0 features over 70 new features, including the ability to more fully deploy decryption, prevent DNS attacks and support Transportation Layer Security 1.3.

Copyright © 2020 IDG Communications, Inc.

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