INDUSTRIAL

Expansion of distributed infrastructure fundamentally transforms the cybersecurity landscape. Data generation and processing increasingly shift toward the edge. As a result, traditional centralized security measures are inadequate due to escalating complexities and scale of emerging threats.

To address these evolving demands, hyperconverged infrastructure is extending beyond traditional data center confines. This extension necessitates adoption of hardware that delivers data-center-class performance while enduring environmental challenges of edge locations.

“The dynamic and varied nature of edge environments requires a new approach to security, one that is more adaptive and intelligent,” explains Stéphane Duburre, Product Line Manager at Kontron, a leader in embedded computing technology. He points to the latest Intel^® Xeon^® processors and Intel^® Arc^™ GPUs as examples. “These advanced processors enable real-time edge AI security analytics, which are crucial for data protection and operational continuity in harsh edge environments.” 

Further complicating the network edge landscape, communication within industrial environments is transitioning to Time-Sensitive Networking (TSN), which supports deterministic messaging on standard Ethernet networks. This advancement facilitates seamless integration of OT and IT networks. But it also expands the attack surface for security threats, requiring a more sophisticated and robust security approach.

Adapting to New Edge AI Security Needs

To address these evolving demands, Kontron developed the ME1310, a high-performance multi-edge platform. Where harsh environments would cause other equipment to fail, the ME1310 exceeds thanks to a 22-core Intel Xeon processor rated for temperatures of -40°C to 65°C. “It sustains performance even under fluctuating or extreme conditions,” Duburre notes.

When more performance is needed, the ME1310 can accommodate two PCIe Gen 4 accelerators, including Intel Arc GPUs for AI acceleration. This adaptability allows for significant enhancements in processing power and speed—critical for applications requiring intensive computation and real-time data processing.

“The dynamic and varied nature of #edge environments requires a new approach to #security, one that is more adaptive and intelligent,” – Stéphane Duburre. @Kontron via @insightdottech

In applications that need high-bandwidth packet processing, the platform’s integrated hardware delivers up to 200 Gigabit Ethernets of HAL2 and HAL3 switching. With support for Precision Time Protocol (PTP) for TSN networks, the ME1310 facilitates data transfers across deterministic networks—maintaining security across increasingly integrated OT and IT environments.

By addressing these challenges, the ME1310 provides a compact, versatile solution that brings data center-level capabilities to the network edge, enabling organizations to navigate the complexities of modern network environments with enhanced operational security and efficiency. 

The Role of AI at the Network Edge

Hyperconverged platforms like the ME1310 lay the foundation for the transformative role of edge AI security. With its ability to learn from and adapt to network activities in real time, AI enables a new dynamic of immediate, autonomous responses to emerging threats. By continually analyzing data, AI significantly improves both the understanding and mitigation of evolving threat behaviors, thereby strengthening overall security measures, according to Duburre.

For AI to be most effective, it must be deployed directly at the network edge. This reduces latency significantly and decreases reliance on centralized data centers, which is vital for timely decision-making in environments where security is critical.

But deploying AI at the network edge introduces unique cybersecurity challenges that differ from traditional data center environments. These include heightened concerns over data privacy, increased vulnerabilities in security devices and network infrastructure, and the complexity of managing security protocols across dispersed and varied edge locations.

But “the integration of Intel Arc GPUs with Intel Xeon D processors enables robust edge AI security capabilities,” explains Duburre. This allows for advanced data analytics and real-time encryption and decryption at the edge.

In manufacturing environments, for example, the ME1310 can use AI to detect and respond to operational anomalies. Duburre elaborates, “Such capabilities allow for the immediate analysis of unexpected stoppages or irregular machine behavior to determine their cause—be it a potential cyberattack or a mechanical failure.”

The Future of Edge AI Security

Looking ahead, the role of hyperconverged platforms like the ME1310 in edge computing is poised to expand significantly. As more organizations leverage IoT and other advanced technologies, demand for localized, powerful computing solutions will continue to rise. Hyperconverged platforms are uniquely positioned to meet these demands, offering compact, versatile solutions that bring data center-level capabilities to the network edge.

For industry professionals navigating the complexities of modern network environments, platforms like the ME1310 can significantly enhance operational security and efficiency. By adopting these sophisticated solutions, businesses can ensure they remain at the cutting edge of technology, prepared to face the challenges of tomorrow’s digital landscapes with confidence and resilience.

This article was edited by Christina Cardoza, Editorial Director for insight.tech.