Iot Network Intrusion Alarming System Using Bat Algorithm & Neural Network

Abstract

The scope of IoT networks has expanded drastically in the modern digital environment. Connectivity along with use of the internet, particularly in the form of data collection and exchange, is a primary characteristic of devices in an IoT network.  This paper has developed a (Bat IOT Network Intrusion Detection System (BINIDS) that alarms for the intrusion in the IOT network. Paper has work on the input dataset for improving the learning of neural network. Dataset optimization was done by BAT algorithm. Input features were cluster into two category selected and rejected. All selected features were processed to train the neural network. Experiment was done on real IOT dataset under different testing size. Result shows that proposed model has improved the work performance.