Byte-level encoding of network flows into RGB images improves intrusion detection accuracy by up to 15.6% on UNSW-NB15 using convolutional models.
Hae-hrl: A network intrusion detection system utilizing a novel autoencoder and a hybrid enhanced lstm-cnn- based residual network
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A Novel Byte-Level Flow-to-Image Encoding Method for Network Intrusion Detection Systems
Byte-level encoding of network flows into RGB images improves intrusion detection accuracy by up to 15.6% on UNSW-NB15 using convolutional models.