Securing Critical Infrastructure & the Mobile Economy with AI-Native Network Intelligence

A suite of distributed AI privacy-preserving security analytics offering early detection and rapid mitigation of threats, enabling network functions to autonomously and safely adapt their policies and behaviour in response to evolving conditions, with rigorous guarantees. 

Formal verification embedded into the control-plane learning uses a probabilistic model validator and constraint enforcement so that the AI agents never violate safety-critical invariants with adaptive algorithms proving they won’t break determinism or service level agreements as they learn – a key differentiator from unbounded RL approaches.

A lightweight adaptation layer quickly fine-tunes the policy to local conditions with minimal data, achieving sub-10 ms re-convergence allowing truly self-driving networks that learn and adapt in real time without lengthy retraining – a breakthrough for handling 6G’s variability.

Real-time & autonomous security policy and operational parameter adaptation to dynamic threats, while guaranteeing safety-critical performance and resilience in hostile and failing environments.

A secure, low-latency bypass path that implements mitigations without disrupting normal traffic and signed with quantum-resistant cryptography to protect against future quantum attacks on network control channels. The network to evolves defense posture autonomously - guaranteeing stability and safety at every step and preventing any violations of core reliability constraints. 

Neuromodulated prioritisation focuses resources where it matters most; ensuring that even under resource strain, the most dangerous threats are addressed first. The result is a 6G network that is self-healing, self-optimising, and provably trustworthy.

Delivers continuous safety-critical network functions and services under adversarial conditions by hardening and securing the control and data planes against faults and attacks - enabling the network to adaptively optimise fault tolerance and performance on the fly. 

Makes consensus and network control robust against node compromises and transient faults by autonomously tuning fault tolerance levels and sharing learned policies across the network in real-time. Even during coordinated attacks, compromised network functions and services are isolated in milliseconds, preventing cascading failures across the business.

A suite of distributed AI security analytics offering real-time autonomous detection and rapid mitigation of threats while safely adapting policies and behaviour in response to evolving hostile conditions with rigorous performance guarantees.

The proactive defense layer adapts as fast as the threats do using Distributed Federated learning at the edge - ensuring no single point of failure or data leak in the analytics system. Graph-based threat modeling catches complex multi-vector attacks that siloed security tools ignore. Together, these innovations identify and neutralise emerging threats before they escalate.

AI-Driven Mobility Management: Leveraging on-device, RAN, core, and OAM/management AI for seamless cross-domain mobility, predictive resource allocation, anomaly detection, and dynamic path optimization. This allows uninterrupted service for fast-moving fleets, UAVs, or tactical teams. - Secure Multi-Domain Integration: Built-in interoperability between terrestrial 6G, maritime networks, aerospace platforms, and satellite constellations. Enables uninterrupted communications across land, sea, air, and space. - Low-Altitude Economy Enablement: Optimized for new mobility economies, including UAV fleets, high-speed rail, maritime drones, autonomous convoys, and emergency response.