Keeping IoT safe in the future will require securing the networks themselves. Focusing on the devices is a never-ending battle that will only become more burdensome.

May Wang, Senior Distinguished Engineer at Palo Alto Networks

January 21, 2021

5 Min Read

Across the rapidly changing enterprise landscape, Internet of Things (IoT) security is top of mind for most organizations. As cybersecurity leaders, we know that the growing amount of IoT devices means more data and more opportunities for attackers.

The risk that organizations face is exacerbated by the pace of IoT adoption — a forecast from International Data Corporation estimates that there will be 41.6 billion connected IoT devices, or "things," by 2025.

In addition, the COVID-19 pandemic has demolished the enterprise network perimeter. Networks are now highly distributed, including remote branches, mobile employees, and even the home, leaving many organizations with little visibility into these IoT devices and traffic.

Further compounding the issue, these distributed networks of IoT devices, which now include personal IoT devices, are relied upon to carry sensitive enterprise data, with 98% of existing IoT device traffic left unencrypted.

Today's cybersecurity leaders need a new approach, moving past a limited focus on securing connected devices to instead create resilient networks that are ready-made for IoT.

Traditional Security Posture Outdated
Even if we ignore the lack of options for securing IoT devices themselves, there are too many and different types of devices to expect a uniform standard for device security. The challenge of scale and complexity would be impossible to solve.

While traditional IT security is designed to catch threats that have made it past the perimeter, it can take an average of 56 days to catch an attack.

Adding to the list of problems is the reality that maintenance for IoT can be timely, costly, and cumbersome. Imagine needing to individually secure each device on your network as if you had to change the batteries for each one. And imagine needing to do that again throughout the long lifespan of these devices, ensuring each one has up-to-date and secure software and policies.

Seeing and Knowing
With the existence of shadow IoT devices lurking on networks and the enterprise perimeter now encompassing the home, it's essential to know more about your networks and what's connected to them.

This requires more than simply identifying IP addresses. You must go beyond simple inventory measures to understand what kinds of devices are on your network. Knowing what a device is lets you know what it should and should not be doing — for example, a medical imaging machine shouldn't be streaming videos on YouTube.

IoT devices come and go on your networks, brought in by different departments and different people. Organizations need to know at any moment what devices are connected to their networks. The static once- or twice-a-year asset checking is no longer sufficient. 

The benefits of granular visibility go beyond IoT — it's the prerequisite to securing any environment in today's age where the network's permeable wall is the new reality.

Smart Monitoring
The challenges of implementing a device or perimeter-focused approach to security include scale and complexity. Securing data, access, and traffic requires machine learning (ML).

ML is increasingly being used for network monitoring, threat detection, and remediation, but it's just as effective at identifying, monitoring, and protecting IoT devices because it can scale these activities in real time. IoT devices are designed for a fixed set of functionalities, show common patterns, and provide lots of data. IoT device patterns are predictable, and ML picks up patterns better than humans at scale.

Network Segmentation and Zero Trust
Another important best practice is proper network segmentation. For example, when done correctly, IoT devices in critical infrastructure won't be compromised when an employee accidently clicks on a phishing email, or an organization won't be breached when IoT devices like a ventilation system are attacked. Creating these separate zones is important for preventing threats from moving inside the perimeter and makes it easier to control IoT devices.

In recent years, the conversation about zero-trust architecture has been on the rise. In practice, this framework also utilizes network segmentation but includes identity and access management too. Zero trust is a best practice that's reaching mainstream adoption, including one of the nation's largest enterprise networks, the Department of Defense.

While zero trust can be difficult to centrally manage, it creates an additional protection layer across IoT devices because access is limited even if network segmentation strategies fail.

Securing IoT in the Future
Just because you were secure yesterday doesn't mean you're secure today or will be tomorrow. With the pandemic and accelerated digital adoption, the enterprise IT landscape is changing fast.

With IoT spending expected to exceed $1 trillion in 2022 according to IDC, the importance of securing the networks these billions of devices connect to should not rely on traditional security principles or device-focused methodologies.

Keeping IoT safe in the future will require securing the networks themselves. Focusing on the devices is a never-ending battle that will only become more burdensome. A network approach, one that incorporates visibility, access, real-time monitoring, and segmentation, provides the only realistic solution for IT administrators and security professionals.

About the Author(s)

May Wang

Senior Distinguished Engineer at Palo Alto Networks

Dr. May Wang is currently a Senior Distinguished Engineer at Palo Alto Networks. Previously, May was the Co-Founder, Chief Technology Officer (CTO), and board member of Zingbox, which was acquired by Palo Alto Networks in 2019 for its security solutions to Internet of Things (IoT).
Before Palo Alto Networks and Zingbox, May was a Principal Architect in the Cisco CTO office driving new technology initiatives. Her algorithms have been deployed in several of Cisco's best-selling products.
May has been the recipient of numerous awards, including Silicon Valley Women of Influence, Female CxO Trailblazers Award, and several Stevie Awards. She received her Ph.D. from Stanford University in Electrical Engineering.

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