LSTM based Deep Learning Technique to Forecast Internet of Things Attacks in MQTT Protocol

Abstract

Internet of Things networks are becoming more popular for monitoring critical environments of various types, resulting in a large increase in the amount of data transmitted. Because of the large number of linked IoT devices, network and security protocols is a major concern. In the sphere of security, detection systems play a critical role: they are based on cutting-edge algorithms. They can recognize or forecast security attacks using techniques such as machine learning, allowing them to secure the underpinning system. We have depicted some of the Deep Learning based techniques and figured out the best technique called Long Short Term Memory (LSTM) with 87% of accuracy to build the Artificial Intelligence based Interpolation Technique for IoT Environment.