CNN-LSTM: Hybrid Deep Neural Network for Network Intrusion Detection System


The importance of network security to our day-to-day interactions and networks cannot be overstated. The importance of having an efficient intrusion detection system has become paramount due to the fact that attackers are continually developing new methods of attack and the size of networks is continually expanding. Developing an efficient IDS required the implementation of Machine Learning algorithms in a number of studies; however, with the advent of Deep Learning algorithms and artificial neural networks that can generate features automatically without the need for human intervention, researchers began to rely on Deep Learning. During the course of our study, we created a hybrid model of an intrusion detection system by combining the capabilities of two different types of neural networks: the Convolutional Neural Network and the Long Short-Term Memory Network. Both of these networks are able to pull out spatial and temporal features, respectively. In order to improve the performance of the model, we included both a batch normalization layer and a dropout layer. The model was trained with the CIC-IDS 2017 dataset, the UNSW-NB15 dataset, and the WSN-DS dataset. The training was based on the binary and multiclass classifications. The efficiency of the system is determined by the confusion matrix, which takes into account a variety of criteria for assessment, including accuracy, precision, detection rate, F1-score, and false alarm rate (FAR). Experiment results that showed a high detection rate, high accuracy, and a relatively low FAR demonstrated the usefulness of the model that was proposed.

Did you like this research project?

To get this research project Guidelines, Training and Code... Click Here

PROJECT TITLE : Video Dissemination over Hybrid Cellular and Ad Hoc Networks - 2014 ABSTRACT: We study the problem of disseminating videos to mobile users by using a hybrid cellular and ad hoc network. In particular, we formulate
PROJECT TITLE : Sleep Scheduling for Geographic Routing in Duty-Cycled Mobile Sensor Network - 2014 ABSTRACT: Recently, the research focus on geographic routing, a promising routing scheme in wireless sensor networks (WSNs),
PROJECT TITLE : Security Analysis of Handover Key Management in 4G LTESAE Networks - 2014 ABSTRACT: The goal of 3GPP Long Term Evolution/System Architecture Evolution (LTE/SAE) is to move mobile cellular wireless technology
PROJECT TITLE : Secure and Efficient Data Transmission for Cluster-Based Wireless Sensor Networks - 2014 ABSTRACT: Secure data transmission is a critical issue for wireless sensor networks (WSNs). Clustering is an effective
PROJECT TITLE : PSR A Lightweight Proactive Source Routing Protocol For Mobile Ad Hoc Networks - 2014 ABSTRACT: Opportunistic data forwarding has drawn much attention in the research community of multihop wireless networking,

Ready to Complete Your Academic MTech Project Work In Affordable Price ?

Project Enquiry