Anomaly Behavior Analysis for IoT Network Nodes

Abstract

The Internet of Things (IoT) will connect not only computers and mobile devices, but it will also interconnect smart buildings, homes, and cities. The integration of IoT with Fog and Cloud Computing can bring not only the computational requirements, but they also enable IoT services to be pervasive, cost-effective, and can be accessed from anywhere and at any time. In any IoT application, communications are crucial to deliver the required information, for instance to take actions during crisis events. However, IoT components such as Gateways, usually referred as IoT nodes, will introduce major security challenges as they contribute to increase the attack surface, preventing the IoT to deliver accurate information to final users. In this paper, we present a methodology to develop an Intrusion Detection System based on Anomaly Behavior Analysis to detect when an IoT network node is being compromised. Our preliminary experimental results show that our approach accurately detects known and unknown anomalies due to misuses or cyber-attacks, with high detection rate and low false alarms.