Anomalous Power-Usage Behavior Detection from Smart Home Wireless Communications
Jian Mao, Shishi Zhu, Jingdong Bian, Qixiao Lin, Jianwei Liu · Journal of Communications and Information Networks · 2019
With the rapid development of Internet of things (IoT) technologies, smart home systems are getting more and more popular in our daily life. Besides providing convenient functionality and tangible benefits, smart home systems expose users to security risks. In this paper, we proposed SHGuard, an anomaly detection approach based on power usage data exposed from wireless communications in the smart home system. SHGuard monitors and collects the electricity-usage data sent from the smart sockets. Based on the collected data, we developed a method to identify/infer the type of device and formally defined the user behavior pattern according to the device event features, e.g., frequent sequence pattern set, the support degree, the sequence length and the occurrence time of the power changing event. SHGuard extracts and builds the normal behavior pattern during the initialization stage. It continuously infers the smart devices' states by monitoring the electricity usage data and updates the user behavior patterns. Any abnormal behaviors will be detected once the current user behavior pattern deviates from the original pattern. We prototyped our method and evaluated SHGuard using UCI dataset. The experiment results illustrated the efficiency of SHGuard.