Intrusion Detection System for IoT environments using Machine Learning Techniques

The Internet of Things (IoT) is fast becoming the new normal in our everyday lives. The communication of connected devices without requiring human intervention has led to the advent of smart ecosystems or environments. Smart ecosystems are an environment where smart devices or ‘things” are trying to improve the quality of life for their inhabitants by determining the inhabitant’s intent without explicit input. This technological advancement brings with it security concerns concerning confidentiality, integrity, and availability as large data volumes are processed by smart devices. Mainstream security solutions may not work in IoT environments due to their unique nature whereby IoT has different protocols, and they have computational resource limitations. This project seeks to develop an intrusion detection system for IoT environments in an IoT network utilizing a machine learning technique whereby a user is alerted if an anomaly has been detected.