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SI malware detection
How machine learning classifies malicious software from static and dynamic features, where it fails, and how to evaluate it honestly.
Knowledge graph
Knowledge
Background explainers behind the research. Each topic links to the research pages it supports and to neighbouring topics.
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Agentic SI in cybersecurity
How autonomous agents plan analysis and propose mitigation under human oversight, audit trails, and explicit permission models.
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Behavioural malware analysis
Observing what malware does when it runs (process, file, registry, and network behaviour) to complement static indicators.
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Pre-execution threat prediction
Predicting what a file will do, and whether it is dangerous, before it is ever allowed to run.
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Explainable SI for security
Techniques that show why a model or agent reached a decision, so analysts can check it, trust it, and challenge it.
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Malware corpora and datasets
Where research malware comes from, how it is labelled and split, and the biases every corpus carries.