Automatic dataset labelling and feature selection for intrusion detection systems

Correctly labelled datasets are commonly required. Three particular scenarios are highlighted, which showcase this need. When using supervised Intrusion Detection Systems (IDSs), these systems need labelled datasets to be trained. Also, the real nature of the analysed datasets must be known when eva...

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Bibliographic Details
Main Authors: Francisco Aparicio-Navarro, Kostas Kyriakopoulos, David Parish
Format: Default Conference proceeding
Published: 2014
Subjects:
Mechanical engineering not elsewhere classified
Automatic labelling
Feature selection
Genetic algorithm
Network traffic labelling
Unsupervised anomaly IDS
Mechanical Engineering not elsewhere classified
Online Access:https://hdl.handle.net/2134/17479
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