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Unsupervised Detection of APT C&C Channels using Web Request Graphs Pavlov Lamprakis1, Rugger Dargenio1, David Gugelmann1, Vincent Lenders2, Markus Happe1, and Laurent Vanbever1 1 2ETH Zurich, Zurich,
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01
Specify the dataset to be used for unsupervised detection of APT.
02
Preprocess the dataset to remove noise and irrelevant information.
03
Choose an appropriate unsupervised detection algorithm for APT.
04
Train the algorithm using the preprocessed dataset.
05
Evaluate the performance of the trained algorithm using suitable metrics.
06
Make necessary adjustments to the algorithm or dataset if required.
07
Apply the trained algorithm to new data for detecting APT.

Who needs unsupervised detection of apt?

01
Organizations that want to proactively detect advanced persistent threats (APTs) in their network infrastructure.
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Security professionals responsible for monitoring and securing critical systems and data.
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Companies that handle sensitive or valuable information and need to protect it from sophisticated cyber attacks.
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Government agencies and defense organizations concerned with national security.
05
Any entities that aim to enhance their overall cybersecurity posture and prevent APTs from compromising their systems.
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