Sparse Representation and Dictionary Learning for Network Traffic Anomaly Detection

Tomasz Kierul; Michał Kierul; Tomasz Andrysiak; Łukasz Saganowski

doi:10.1007/978-3-030-48256-5_34

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Sparse Representation and Dictionary Learning for Network Traffic Anomaly Detection

Tomasz Kierul Michał Kierul Tomasz Andrysiak Łukasz Saganowski

Year: 2020 Advances in intelligent systems and computing Pages: 344-354 Publisher: Springer Nature

DOI: 10.1007/978-3-030-48256-5_34

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Keywords:

Outlier Anomaly detection Representation (politics) Sparse approximation Computer science Artificial intelligence Set (abstract data type) Pattern recognition (psychology) SIGNAL (programming language) Anomaly (physics) Process (computing) K-SVD Data mining Machine learning

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Anomaly Detection Techniques and Applications

Physical Sciences → Computer Science → Artificial Intelligence

Sparse and Compressive Sensing Techniques

Physical Sciences → Engineering → Computational Mechanics

Image and Signal Denoising Methods

Physical Sciences → Computer Science → Computer Vision and Pattern Recognition

Sparse Representation and Dictionary Learning for Network Traffic Anomaly Detection

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