Security as a service

With the increase in number of Internet connected devices, security and privacy concerns are the major obstacles impeding the widespread adoption of Internet of Things (IoT). Securing IoT has become a huge area of concern for all, including the consumers, organizations as well as the government. While attacks on any system cannot be fully prevented forever, real-time detection of the attacks are critical to defend the systems in an effective manner. In this paper, we propose a novel intrusion detection system that uses machine learning algorithms to detect security anomalies in IoT networks. This detection platform provides security as a service and facilitates interoperability between various network communication protocols used in IoT. In this paper, we provide a framework of the proposed system and discuss the intrusion detection process in detail.