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Experimenting with anomaly detection features for performance

Supervisors

Suitable for

MSc in Computer Science
Computer Science, Part B 2017-18
Mathematics and Computer Science, Part C
Computer Science and Philosophy, Part C
Computer Science, Part C

Abstract

Considering relative detection performance using different feature sets, and different anomalies of interest, in the face of varying attacks. Conducted with a view to exploring the minimal sets that would result in the threat detection, and producing guidance that is aimed at determining the critical datasets required for the control to be effective.