S-Flex Tech Underpins euNetworks’ High-Capacity Quantum Shield

euNetworks has launched Quantum Shield, a new private connectivity service utilizing Adtran’s encrypted optical transport technology and S-Flex technology to secure data center connections across its pan-European network. The service is designed for organizations facing increasingly stringent security demands and evolving cybersecurity regulations like DORA and NIS2, which are raising expectations for encryption and data protection. Quantum Shield combines high-capacity dedicated infrastructure with real-time fiber monitoring and quantum-resistant encryption at the optical layer, safeguarding sensitive traffic. “Data center connectivity sits at the heart of our customers’ operations, particularly in environments where security and resilience are non-negotiable,” said Marisa Trisolino, CEO of euNetworks, as the company responds to the EU’s coordinated post-quantum cryptography roadmap targeting high-risk infrastructure migration.

Adtran’s Optical Transport Technology Powers Quantum Shield Service

This isn’t simply about adding encryption; it’s a comprehensive approach integrating advanced cryptography with continuous monitoring at the optical layer, designed to deliver protection for sensitive data traversing the continent. The launch arrives as organizations across Europe accelerate plans to secure data in transit, driven by increasingly stringent cybersecurity regulations and the looming threat of quantum computing. The EU’s coordinated post-quantum cryptography roadmap targets migration of high-risk and critical infrastructure environments, while regulations including DORA and NIS2 are increasing expectations for encryption, crypto-agility and the protection of sensitive traffic. euNetworks addresses these demands by offering Quantum Shield as an additional security layer for its Private Connect MOFN solution, providing organizations with enhanced control over their data and a dedicated, managed network infrastructure.

This service utilizes Adtran’s FSP optical transport platform, incorporating S-Flex technology to support high-capacity encrypted data center interconnect services, and harnesses post-quantum cryptography aligned with NIST standards. “We’re committed to providing customers with connectivity that meets increasingly stringent security requirements and chose to partner with Adtran because they bring deep expertise in optical networking and a practical understanding of how private infrastructure is built and operated at scale,” said Christoph Glingener, CTO of Adtran. Adtran’s ALM solution further enhances security by instantly detecting and precisely locating fiber-tapping events, providing complete transparency and control over data security across the optical layer.

Built upon euNetworks’ existing pan-European network, the service augments current infrastructure to deliver secure, scalable data center connectivity, offering enterprises a proactive defense against emerging threats. Integrating encryption directly into the physical layer of the network is a crucial distinction as security paradigms shift, ensuring current compliance while also providing a crypto-agile framework capable of adapting to evolving cybersecurity standards.

We’re committed to providing customers with connectivity that meets increasingly stringent security requirements and chose to partner with Adtran because they bring deep expertise in optical networking and a practical understanding of how private infrastructure is built and operated at scale.

Marisa Trisolino, CEO of euNetworks
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Ivy Delaney

Ivy Delaney has been working with neural networks and machine learning since the mid-nineties, back when a couple of hidden layers and a long afternoon of training counted as ambitious. She has watched the field go from academic curiosity to the thing quietly running underneath everything, and she brings that long view to quantum computing. For Quantum Zeitgeist she covers the ground where the two fields meet. That means quantum machine learning and the variational algorithms it leans on, and it also means the less glamorous but more interesting story of classical machine learning already doing real work inside quantum machines, decoding error-correcting codes, calibrating noisy hardware and learning the error models that simulators depend on. She writes about the hardware those algorithms have to run on too, and about the post-quantum cryptography scramble that the same hardware has set off. Her stories typically start with the paper, whether that is peer-reviewed work, conference proceedings or an arXiv preprint, with the source linked so you can hold a claim up against the research it came from. She is unimpressed by benchmarks that will not say what they beat, and by demonstrations that only work in the press release.

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