  Internet of Things (IoT) has become the most promising technology for service
automation, monitoring, and interconnection, etc. However, the security and
privacy issues caused by IoT arouse concerns. Recent research focuses on
addressing security issues by looking inside platform and apps. In this work,
we creatively change the angle to consider security problems from a wireless
context perspective. We propose a novel framework called IoTGaze, which can
discover potential anomalies and vulnerabilities in the IoT system via wireless
traffic analysis. By sniffing the encrypted wireless traffic, IoTGaze can
automatically identify the sequential interaction of events between apps and
devices. We discover the temporal event dependencies and generate the Wireless
Context for the IoT system. Meanwhile, we extract the IoT Context, which
reflects user's expectation, from IoT apps' descriptions and user interfaces.
If the wireless context does not match the expected IoT context, IoTGaze
reports an anomaly. Furthermore, IoTGaze can discover the vulnerabilities
caused by the inter-app interaction via hidden channels, such as temperature
and illuminance. We provide a proof-of-concept implementation and evaluation of
our framework on the Samsung SmartThings platform. The evaluation shows that
IoTGaze can effectively discover anomalies and vulnerabilities, thereby greatly
enhancing the security of IoT systems.
