Palo Alto Networks Expands IoT Security through Acquisition

U.S. security network giant Palo Alto Networks recently announced its intent to acquire Internet of Things (IoT) security outfit Zingbox for US$75 million. The acquisition is set to close in 1Q 2020. The announcement was made during the firm’s financial result reporting where it reported 28% Year-over-Year (YoY) revenue growth for 2019 to $2.9 billion, a successful result of Palo Alto’s bid to extend its Total Addressable Market (TAM) to new markets. The Zingbox acquisition fits right into this strategy.

Palo Alto Networks has built its reputation as one of the leaders in cybersecurity from a network perspective. The firm has one of the best firewall solutions currently in the market. It has extended its security capabilities to the cloud (Prisma), 5G/IoT offerings, and most recently has adopted Cortex, which leverages Artificial Intelligence (AI) to spot and remediate security threats through large data lakes that collect and analyze enterprise data, to enhance its security proposition. 

Zingbox’s solution is also AI-powered. It uses a three-tier machine learning algorithm to identify devices (device category, profile, and instance) before leveraging behavioral analysis to establish a baseline for typical behavior. The firm has a huge repository of thousands of devices that include information on context, type, behavior, etc. Additional tools allow for the creation of groups for categorizing the devices and policies to manage them. Insights are provided back to the enterprise to help them optimize device usage. As such, Zingbox does not require the installation of either hardware (appliances) or software (agents) in order to run the solution, significantly simplifying the task of tackling IoT threats.

The acquisition fits in nicely with Palo Alto Networks’ ongoing efforts to tackle IoT security, which have been limited to date. It currently focuses on cellular network security and offers a 5G-ready next generation firewall. Zingbox’s technology will allow Palo Alto Networks to expand its IoT security portfolio significantly and complement the Cortex Platform.

Enterprise cybersecurity companies have been trying to solve the IoT security issue for some time now, and not many have been successful, not least because the IoT landscape is so broad and diverse that traditional network security solutions are not capable of capturing the wide variety and breadth of IoT traffic and devices. This is especially true for those leveraging cellular connectivity. Much of the network security market has evolved around dedicated physical security appliances, and the advent of the cloud was a significant challenge for most security vendors. Having managed to virtualize many of their tools, they are now faced with the challenge of having to add new features that can provide visibility into IoT devices and networks, intelligence about threats, and security solutions to protect them.

The first generation of IoT security startups leveraged either software agents to that end or required the manual input of device information into network security appliances for effective protection. With the explosion of IoT devices and traffic, these methods are simply not cost-effective or easily undertaken. The use of AI provides a much better alternative to understanding the IoT, and the vast amounts of data generated only serve to improve machine learning algorithms. Certainly, there is still a lot of work that needs to go into developing these algorithms and training the models but, over time, companies like Zingbox have built rich repositories. Together with the algorithms, they form the real value of the overlying solution and make attractive acquisition targets for large cybersecurity vendors that have yet to expand fully into IoT security. Other firms have taken a similar plunge—see ABI Insight Cisco to Enhance Industrial Security Offerings with Sentryo Acquisition (IN-5535), for example—so those startups that have created the right mix of AI and data will find themselves in high demand.