Intrusion Detection using Recurrent Neural Networks

Chandini S B
2020 International Journal for Research in Applied Science and Engineering Technology  
When it comes to large data sets, deep learning methodology plays a more important role in data science. In this paper we investigate attacks of intrusion detection. Detection of intrusion Performs an important function in the protection of Privacy of knowledge and main technologies is to reliably Identification different network intrusion attacks. In this paper, we research how to view a deep learning-dependent interruption location system, and we're going to suggest a deep learning method for
more » ... interruption attack discovery Use of repetitive neural networks (RNN-IDS) algorithm. In this project we are going to analyze the KDD datasets which consists of 44 features based on feature we are going to apply the classification algorithm (Recurrent neural network) which helps in training the data and helps in finding the accuracy. We compare it with those of decision tree, help for vector machines and other machine learning approaches suggested by previous benchmark researchers.
doi:10.22214/ijraset.2020.6335 fatcat:wwkxo63vezhdhirhbkxlrtraum