Applying long short-term memory recurrent neural networks to intrusion detection

Applying long short-term memory recurrent neural networks to intrusion detection

We claim that modelling network traffic as a time series with a supervised learning approach, using known genuine and malicious behaviour, improves intrusion detection. To substantiate this, we trained long short-term memory (LSTM) recurrent neural networks with the training data provided by the DAR...

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Bibliographic Details
Main Author: Ralf C. Staudemeyer
Format: Article
Language:English
Published: South African Institute of Computer Scientists and Information Technologists 2015-07-01
Series:South African Computer Journal
Subjects:
long short-term memory, recurrent neural network, KDD Cup ’99, intrusion detection systems, machine learning, time series analysis, receiver operating characteristic
Online Access:http://sacj.cs.uct.ac.za/index.php/sacj/article/view/248

Internet

http://sacj.cs.uct.ac.za/index.php/sacj/article/view/248

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