A Host-Based Intrusion Detection and Mitigation Framework for Smart Home IoT Using OpenFlow

Abstract

Smart devices are gaining popularity in our homes with the promise to make our lives easier and more comfortable. However, the increased deployment of such smart devices brings an increase in potential security risks. In this work, we propose an intrusion detection and mitigation framework, called IoT-IDM, to provide a network-level protection for smart devices deployed in home environments. IoT-IDM monitors the network activities of intended smart devices within the home and investigates whether there is any suspicious or malicious activity. Once an intrusion is detected, it is also capable of blocking the intruder in accessing the victim device on the fly. The modular design of IoT-IDM gives its users the flexibility to employ customized machine learning techniques for detection based on learned signature patterns of known attacks. Software-defined networking technology and its enabling communication protocol, OpenFlow, are used to realise this framework. Finally, a prototype of IoT-IDM is developed and the applicability and efficiency of proposed framework demonstrated through a real IoT device: a smart light bulb.