THREATBYTESTM research
Research questions
Five research questions govern experiments, datasets, and evaluation, covering predictive accuracy, intent inference, hybrid SI design, governed mitigation, and community-submitted learning.
Research questions01
1. Can SI models integrating deep learning, reinforcement learning, and reasoning modules accurately predict previously unseen malware behaviours before execution?
2. How can agentic cognitive SI infer malware intent from incomplete or evolving behavioural indicators?
3. What combination of pattern recognition, reinforcement learning, and reasoning strategies yields optimal predictive and preventive malware defence?
4. How can autonomous SI agents execute reliable, pre-emptive mitigation actions while maintaining low false-positive rates and avoiding collateral disruption?
5. How can community-submitted malware samples enhance the learning and predictive capability of the agentic SI framework?Traceability02
Each question maps to documented experiments, datasets, and evaluation metrics published through the research platform as results mature.