Research

Current research focus areas for VYXNOS. Work is in progress; outcomes will inform architecture and implementation.

• Autonomous Defense Loop

  Closed-loop systems that ingest telemetry, evaluate policy, and apply corrective actions with minimal human intervention. Research includes safety bounds, rollback semantics, and auditability.

• Reinforcement Learning for Policy Optimization

  Using RL to tune policy parameters and response strategies from outcome feedback. Focus on sample efficiency, constraint satisfaction, and interpretability of learned behavior.

• Edge-native ONNX Inference

  Running ONNX models at the edge for low-latency detection and classification. Work on model compression, quantization, and runtime integration with gateway and control plane.

• WASM-based Multi-tenant Sandboxing

  WebAssembly as an isolation boundary for tenant-supplied or third-party logic. Evaluation of WASMtime and related runtimes for security, performance, and resource limits.

• Privacy-preserving Federated Threat Intelligence

  Mechanisms to share threat indicators and model updates across organizations without centralizing raw data. Exploration of secure aggregation, differential privacy, and federated learning patterns.