Security Is Key When AI Meets 5G

With the vast number of connections it will enable, 5G networks will have increased attack surface that adversaries can try to exploit.


5G represents a revolution in mobile technology with performance that will rival that of wireline networks. Relative to its 4G predecessor, 5G promises 10X the data rate, 100X the efficiency, and 1000X the capacity, at 1/100th the latency. With 1Gbps speed at 1ms latency, 5G makes it possible to offer a host of real-time applications and services.

Real-time is critical, because in parallel to the roll out of 5G runs the rise of artificial intelligence (AI). As AI increasingly moves into controlling devices in the physical world, from delivery drones to autonomous vehicles, the high-speed, Ultra-reliable Low Latency Communication (uRLLC) links that 5G provides become a critical enabler.

In fact, most of 5G’s “users” will be the things of the Internet of Things (IoT). We human users will benefit both from the improved high-data rate mobile experience of 5G, and from the AI-enabled and 5G-connected devices that will make our world smarter, safer and more convenient.

The vast number of 5G-connected IoT devices will generate a torrent of data. In a true virtuous cycle, 5G networks will make possible the collection of this enormous quantity of data, AI training requires these vast amounts of data, and AI will be the only practical means of managing all this data.

In this way, the success of 5G and AI are inextricably tied. While independently they create enormous value, together they create exponentially more. And with greatly increasing value, the imperative to protect said value rises commensurately.

By their very nature, 5G networks will have increased attack surface that adversaries will try to exploit. For instance, in order to meet its latency targets, 5G architecture pushes more computing to the edge of the network. For AI, this will enable both inference and even training at the edge. This distributes valuable AI algorithms (more opportunities for attack) and takes them out of the hardened data center environment (a lower barrier for attack).

Further, it will be critical to safeguard the data carried by 5G networks. With AI-powered devices flying our skies, driving our roads and protecting our neighborhoods, an attack which compromises the data coursing to and from these devices can threaten privacy, property and personal safety.

Thirty years of the web have made it abundantly clear that software-level security alone is not up to the task of protecting the real-time, always-on world of 5G and AI. The whack-a-mole game of patching software vulnerabilities is far too risky given the stakes. Protecting 5G networks, and the AI-enabled IoT devices that depend on them, will require security anchored in hardware.

Secure processing cores embedded in the chips at the heart of 5G and AI devices will enable a system-level security architecture that can protect the entire network. Provisioned at time of manufacture, these trusted devices can attest to the validity of electronic systems and the data they process and communicate. Hardened against direct and side-channel attacks, they extend protection to the edge and to end-point devices. Intelligent and flexible, they can be managed in the field to adapt to an evolving threat landscape.

There are incredible synergies to be realized when 5G meets AI. It is imperative that security anchored in hardware is part of the fundamental design philosophy of 5G and AI systems given the great value at issue.

Additional Resources:
Webinars: Implementing Strong Security for AI/ML Accelerators: Part One, Part Two, Part Three

Rambus CryptoManager Root of Trust

Rambus Protocol Engines

Rambus Provisioning and Key Management

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