Time-frequency analysis and autoencoder approach for network traffic anomaly detection

Time-frequency analysis and autoencoder approach for network traffic anomaly detection

Detection of anomalies in network traffic is critical to mitigating cyber threats. This study integrates continuous wavelet transform (CWT), discrete-time Fourier transform (DTFT), short-time Fourier transform (STFT), and autoencoders to identify anomalous network behaviour. It conducts time- freque...

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Bibliographic Details
Main Authors: Ruchira Purohit, Satish Kumar, Sameer Sayyad, Ketan Kotecha
Format: Article
Language:English
Published: Elsevier 2025-06-01
Series:MethodsX
Subjects:
Hybrid Time-Frequency Analysis and Autoencoder
Online Access:http://www.sciencedirect.com/science/article/pii/S2215016125000755

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http://www.sciencedirect.com/science/article/pii/S2215016125000755

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