Effective Intrusion Detection using Deeper Recurrent Neural Networks
Praveen Kumar Kollu · International Journal of Advanced Trends in Computer Science and Engineering · 2019
Computer networks are susceptible to a variety of security threats.With the ever growing number of devices and people that are connecting to the network, it has become an utmost priority to defend these networks at a large scale.The constant changing nature of the networks and the increase in the type of attacks have made the traditional approaches to intrusion detection obsolete.In this paper, we are proposing a deeper recurrent neural network based approach for intrusion detection in large scale networks.The proposed model uses independent neurons in each layer to construct a deeper recurrent neural network.It helps in faster training and classification time as well as adaptability and scalability to dynamic environments.To evaluate our proposed model, CICIDS 2017 dataset was used to implement and compare against popular deep learning based approaches in network intrusion detection.The experiments have shown promising results that our proposed model can produce improved results over existing approaches.