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Edge AI: Addressing Industrial Cybersecurity Challenges

industrial cybersecurityCyber threats in the industrial sector are a growing problem—and there are no quick fixes.

Several factors contribute to this challenge. The rise of the Industrial Internet of Things (IIoT) has connected all kinds of manufacturing equipment, control systems, and sensors to the network for the first time—greatly expanding the attack surface available to malicious actors. In addition, operational technology (OT) assets often rely on proprietary data transfer protocols and unpatched legacy operating systems, making them harder to secure than standard IT systems. And, like businesses in almost every other sector, manufacturers face a shortage of skilled security personnel, making it difficult for their IT and cybersecurity teams to cope with the increasing volume of threats.

In this difficult landscape, manufacturers require innovative solutions to address their ongoing OT security issues—and the application of artificial intelligence (AI) shows promise. But AI-based solutions can be challenging in themselves to implement in industrial settings.

“To apply AI effectively to industrial cybersecurity, you need high-performance edge computing capabilities to manage the intensive inferencing workloads,” says Tiana Shao, Product Marketing at AEWIN Technologies, a networking and edge computing provider with a wide range of solutions for the industrial sector. “Industrial environments also have unusually demanding requirements for scalability, flexibility, and ruggedness.”

The good news for the sector is that companies like AEWIN have now begun to offer edge hardware appliances that make it far easier for system integrators (SIs) and manufacturers to deploy AI-enabled cybersecurity solutions in factories. Based on next-generation processors and advanced software technologies, these solutions help security teams wield AI more effectively in the fight against cyber threat actors.

Beyond Automation: AI in Industrial Cybersecurity

While AI is not a “magic bullet” for industrial cybersecurity, it does introduce a new element to cybersecurity solutions: the ability to learn.

“AI in cybersecurity goes beyond mere security automation, because over time it can develop an understanding of what constitutes ‘normal’ user behavior and network activity,” says Shao. “AI can be used to analyze massive data sets in order to identify trends, flag risks, and detect anomalous events more effectively.”

That unique capability offers security teams some significant advantages. It gives them a better chance of detecting certain kinds of malicious activity that a legacy approach might miss. Establishing a baseline of “normal” activity also makes it possible to reduce the number of time-consuming false positive alerts. 

“To apply #AI effectively to industrial #cybersecurity, you need high-performance #edge computing capabilities to manage the intensive inferencing workloads.” – Tiana Shao, @IPC_aewin via @insightdottech

Perhaps most important, through the methodology of searching for threats by identifying deviations from expected behavior—rather than by relying solely on rule-based approaches that attempt to match system activity or files to known threats—AI-assisted security tools can help security teams detect new and emerging cyber threats with greater accuracy. 

Industrial Cybersecurity: It Takes a Team

AEWIN’s experience with an OT system integrator in the United States is a good demonstration of this.

The SI wanted to offer manufacturers a better way to detect sophisticated cybercriminal activity and speed response times, but this was difficult to accomplish using traditional methodologies. Newer threats, especially those that work by abusing or mimicking legitimate system operations, were simply getting lost in the “noise” of routine system activity, and thus overlooked. 

Working with AEWIN, the SI developed a security solution that leveraged AI to analyze system behavior and learn what constituted “normal” so that deviations could be spotted more easily. The SI also used AI to help orchestrate the response across multiple controls and integrate new threat intelligence dynamically to improve defenses. 

The result was an enhanced cybersecurity solution that could learn from historical data, identify patterns of activity, and detect cyberattacks that were being missed by traditional tools—while also responding to threats more quickly and becoming even more effective over time. 

AEWIN’s experience highlights the benefits of partnerships between cybersecurity specialists and hardware providers—a phenomenon mirrored by AEWIN’s own experience with Intel as a technology partner.

In developing its SCB-1942 edge hardware appliance, the company worked with Intel to develop a powerful, flexible computing platform capable of handling the rigorous demands of AI in industrial cybersecurity. The device was constructed atop Intel® Xeon® Scalable processors, which offer up to 64 CPU cores and increased PCIe lanes for greater expandability. 

The underlying hardware is further augmented by Intel’s range of AI accelerators. This includes Intel® Advanced Matrix Extension (Intel® AMX), which improves deep-learning training and inferencing, and Intel® Advanced Vector Extensions 512 (Intel® AVX-512), a set of new instructions that help boost the performance of the machine learning workloads used for intelligent cyber threat detection. 

“Our relationship with Intel gave us extensive technical support and early access to advanced processors, helping us bring a scalable, high-performance edge computing solution to market faster,” says Shao. “Intel processors deliver remarkable performance and can meet the demanding workloads required to use AI to analyze network traffic in real time, perform deep packet inspection, and apply security policies automatically.”

A Future Toward Secure Digital Transformation in Manufacturing

As more and more manufacturers embrace digital transformation, it is expected that there will be an increase in cyber threats in industry—and that cybercriminals will develop new attacks as well. Luckily, AI can help skilled security practitioners respond to evolving threats more quickly and effectively than ever before—while purpose-built hardware appliances can help security teams deploy their AI tools in manufacturing settings more easily.

“We believe that the use of AI in industrial cybersecurity is only going to increase in the coming years,” says Shao. “Our mission is to support our customers by providing reliable, scalable, cutting-edge systems for this fast-growing market.”

This article was edited by Christina Cardoza, Editorial Director for