A containerised approach to labelled C&C traffic

Vitenskapelig publikasjon 2022

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Engelsk

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Markus Leira Asprusten Julie Lidahl Gjerstad Gudmund Grov Espen Hammer Kjellstadli Robert Flood Henry Clausen David Aspinall
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 container-based approach for simulating and labelling C&C traffic of real malware through a proof-of-concept implementation.

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