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A containerised approach to labelled C&C traffic
(2022-01-24)
A challenge for data-driven methods for intrusion detection is the availability of high quality and realistic data, with ground truth at suitable level of granularity to train machine learning models. Here, we explore a ...
CBAM: A Contextual Model for Network Anomaly Detection
(2021)
Anomaly-based intrusion detection methods aim to combat the increasing rate of zero-day attacks, however, their success is currently restricted to the detection of high-volume attacks using aggregated traffic features. ...