Reconstruction-based LSTM-Autoencoder for Anomaly-based DDoS Attack Detection over Multivariate Time-Series Data. (arXiv:2305.09475v1 [cs.CR])

A Distributed Denial-of-service (DDoS) attack is a malicious attempt to
disrupt the regular traffic of a targeted server, service, or network by
sending a flood of traffic to overwhelm the target or its surrounding
infrastructure. As technology improves, new attacks have been developed by
hackers. Traditional statistical and shallow machine learning techniques can
detect superficial anomalies based on shallow data and feature selection,
however, these approaches cannot detect unseen DDoS attacks. In this context,
we propose a reconstruction-based anomaly detection …

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