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Evidence-driven R&D

Applied research designed to survive technical scrutiny.

CyberAI structures research around explicit assumptions, reproducible implementation, measurable evidence and an honest technology-readiness path.

CyberAI Research / Applied security systemsGroningen · 2026
Featured research direction

Trustworthy and secure AI

Model integrity, adversarial robustness, privacy, secure deployment and evidence-based AI governance.
02 / RESEARCH DIRECTION

Cloud–edge cyber resilience

Threat monitoring, distributed trust and lightweight protection across cloud-native and edge environments.

03 / RESEARCH DIRECTION

Connected and cyber-physical systems

Behavioural risk signals, device manipulation detection and operational response.

04 / RESEARCH DIRECTION

AI-assisted security operations

Evidence-oriented threat prioritisation, analyst support and transparent decision chains.

Research discipline

Every claim must connect to method, implementation and evidence.

We avoid presenting concepts as products or preliminary demonstrations as proven deployment results.

Problem framing

Threat, system, actors, assumptions and security objectives.

Method & implementation

Documented analytical choices, architecture and reproducible artefacts.

Evaluation

Data, baselines, metrics, limitations and bounded interpretation.

Research question

Assumptions and method are defined.

Laboratory prototype

Core behaviour is demonstrated under controlled conditions.

Partner validation

Evidence is tested against partner context and constraints.

Deployment preparation

Integration, governance and operational controls are addressed.