Consider a Fabric Approach to Edge Computing Security

In our last post, we discussed how the Internet of Things (IoT) is driving increased adoption of edge computing solutions that move processing power closer to data sources. While this shift facilitates real-time analysis of IoT data, it also expands the potential attack surface and will require organizations to rethink their approach to security.

In the edge computing model, IoT data from sensors and other connected devices is collected and analyzed locally in dozens of so-called micro data centers — standalone, rack-level systems deployed outside the primary data center. All of these edge devices are potential entry points for malware and other cyberattacks.

While these self-contained micro data centers typically include built-in security measures, they nonetheless place a strain on organizations by contributing to overall security sprawl. The ZK Research 2017 Security Survey found that businesses have, on average, 32 separate security tools deployed. That’s a heavy management burden that will only get worse as organizations deploy edge devices with separate security features.

It seems clear that managing and monitoring all these security tools can no longer be reliably done with manual processes. As a result, industry analysts say, edge computing environments need fabric-based solutions that can automatically synchronize security resources to enforce policies and integrate the management of security resources through a single console. A security fabric should also be able to coordinate responses to threats detected anywhere in the network.

The latest version of Fortinet’s Security Fabric architecture delivers hundreds of new features and capabilities that were designed to provide exactly that type of protection. FortiOS 6.0 features the broad visibility, integrated threat intelligence and automated responses required to integrate security across the entire distributed network, including IoT devices and edge computing resources as well as multi-cloud environments.

Because the fabric functions as a single entity, it provides awareness and visibility across the entire infrastructure. This reduces complexity and costs while increasing management efficiencies through a single-pane-of-glass view. This breadth of security intelligence — coupled with sophisticated, scalable and rapid analytics — provides an actionable security architecture with the ability to rapidly detect and mitigate threats wherever they occur.

Advanced artificial intelligence and machine learning features analyze and identify threats with speed, agility and accuracy to provide threat detection and automated remediation at machine scale. Using advanced algorithms, the system can analyze millions of threat samples per week to identify the unique malicious features of each sample. It proactively determines if a new sample poses a threat and generates threat intelligence that updates defensive signatures across the entire Fortinet Security Fabric.

A new Fabric Agent sends telemetry data from all IoT and edge endpoints to the Security Fabric for deeper insight on what is running on the devices, and identification of vulnerabilities. The fabric also allows IT to segment IoT devices and communications into policy-driven groups and grant baseline privileges suitable for specific risk profiles. Other features allow IoT and edge devices to be internally segmented so IT can apply security policies based on the specific device type and network access requirements.

As organizations embrace digital transformation initiatives such as IoT and multi-cloud networks to achieve business agility, automation and scale, the increased connectedness is creating a much larger attack vector. Shifting from manual support of dozens of standalone security measures to an automated, comprehensive security fabric can better protect business data spread across these complex environments.