Why Machine Learning is Crucial to Discovering and Securing IoT devices

In this week's Security Speakeasy discussion, Minakshi Sehgal, Sr. Product Marketing Manager for Palo Alto Networks, sat down with Dr. May Wang to discuss the importance of Machine Learning (ML) in discovering and securing IoT devices.

Dr. Wang, co-founder and a visionary of former Zingbox—which became a part of Palo Alto Networks in late 2019 and was rebranded as our IoT Security solution—is a leading expert on ML and its future in cybersecurity. In 2021, fingerprints and signature-based securities are not enough to mitigate risk. From scalability to self-protection, Dr. Wang drives home the importance of ML-based and Cloud-based security solutions.

"Machine Learning can automatically build models and know what [IoT] normal behaviors should be, and can easily catch their abnormal behaviors. Machine Learning is also easier than human beings in terms of scaling-up ... That's why, from our years of R&D and years of real-world deployment to protect tens of millions of devices, we see that Machine Learning provides a very effective solution to securing all IoT devices."
—Dr. May Wang

Learn more by watching the video below. Can't get enough? Check Palo Alto Networks' Comprehensive IoT Security solution and read Unit 42's latest IoT threat report!