Computer network intrusion detection using sequential LSTM Neural Networks autoencoders

Pages: 1 - 4
Published: May 2, 2018
Abstract
In this paper, we introduce a sequential autoencoder framework using long short term memory (LSTM) neural network for computer network intrusion detection. We exploit the dimensionality reduction and feature extraction property of the autoencoder framework to efficiently carry out the reconstruction process. Furthermore, we use the LSTM networks to handle the sequential nature of the computer network data. We assign a threshold value based on...
Paper Details
Title
Computer network intrusion detection using sequential LSTM Neural Networks autoencoders
Published Date
May 2, 2018
Journal
Pages
1 - 4
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