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.