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Chinese Automotive Manufacturer

Zero-Trust Security from Fortinet Enables IT/OT Convergence for Chinese Automotive Manufacturer

In a test that used a virus sample provided by a third party, Fortinet’s detection rate was above 80% out-of-the box and reached 95% when optimized. The detection rate for competing products, on the other hand, was just 20%.

 

Auto manufacturers are benefiting from unprecedented operational efficiencies from the convergence of information technology (IT) and operational technology (OT). However, the resulting expanded network edge has also led to a significant increase in cyberattacks. This is of considerable concern to manufacturers, as many of the industrial control systems in place today have not been designed with security as top of mind. As digital innovation for one China-based automotive manufacturer ramped up, OT security became a top priority.

Fortinet’s solution for the manufacturer, comprised of FortiGate Next-Generation Firewalls, strengthened the company’s ability to identify and control unknown threats, while also enhancing its incident response to ensure the timely reporting of security breaches. Through microsegmentation, the automotive manufacturer is embracing a zero-trust security framework. The company’s new OT security infrastructure provides a clear demarcation of the whole network. In addition, Fortinet’s support of a wide range of industrial communication protocols helps for monitoring the full OT/IT network and assets, enabling anomaly detection at deeper OT layers for a stronger security posture.

See how this manufacturer raised its OT security benchmark, enabling the digital innovations crucial to its operations in this case study.

Business Impact

 

segmentation icon

Robust zoning and segmentation to stop malware spreading across networks, enabling the convergence of OT and IT

Icon automation

Zero-trust security framework that enables safe manufacturing innovation comprised of increasing automation

Monitoring

Monitoring of the full OT/IT network and assets, enabling anomaly detection at deeper OT layers

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