Читать книгу Intelligent Network Management and Control - Badr Benmammar - Страница 22

Artificial neural networks learn to predict the behavior of various system users. If correctly designed and implemented, neural networks can potentially solve several problems encountered by rule-based approaches. The main advantage of neural networks is their tolerance to inaccurate data and uncertain information and their capacity to deduce solutions without previous knowledge on data regularities. Cunningham and Lippmann (2000) of MIT Lincoln Laboratory conducted a number of tests using neural networks. The system searched for attack-specific key words specific in the network traffic. In Ponkarthika and Saraswathy (2018), a model of intrusion detection system is explored as a function of deep learning. Long–short term memory (LSTM) architecture was applied to a recurrent neural network for the learning of an intrusion detection system using the KDD Cup 1999 dataset.