A Method for Countering Snooping-Based Side Channel Attacks in Smart Home Applications

Abstract

In recent years, with the rapid development of the Internet of Things (IoT), the information technology has been widely used in smart home applications. On the other hand, smart home technology closely related to people’s privacy, which is not much considered by smart home vendors, making the privacy protection of smart home a hot research topic. Traditional encryption methods can ensure the security of the transmission process, but it can hardly resist the side channel attacks. Adversaries can analyze the radio frequency signals of wireless sensors and timestamp series to acquire the Activity of Daily Living (ADL). The most simple and efficient way to counter side channel attacks is to add noise into the transmitted data sequence. In this paper, we propose an improved method based on Logistic Regression (LR), which can be adapted to network status to protect the privacy of residents in smart home environments. Compared with other similar approaches, our method has the advantage of low energy consumption, low latency, strong adaptability and good effect of privacy protection.