关键词: 加密流量, 隐蔽智能摄像头检测, WiFi, 机器学习, 物联网安全

Abstract: With the rapid development of Internet of Things technology, smart cameras are widely used in personal and public safety due to ease of use and low cost. However, the issue of unauthorized video recording also raises concerns about privacy and security, so the detection and identification of hidden smart cameras in specific environments is of great significance. Existing covert smart camera detection methods cannot accurately detect cameras that delay data transmission or save data locally, because these methods rely primarily on camera audio and video network traffic generated when users view surveillance. To solve this problem, this paper proposes a covert intelligent camera detection method based on device WiFi reconnection traffic. The method uses MDK4 flooding attacks to make all smart devices connected to WiFi hotspots offline and reconnect, then sniffs and analyzes the encrypted traffic generated during the process of smart devices reconnecting to WiFi in the environment, and uses machine learning methods to detect hidden smart camera devices. The experimental results show that even without WiFi access, this method still has a high detection accuracy for hidden smart camera devices with delayed transmission or data stored locally.

Key words: encrypted traffic, hidden smart cameras detection, WiFi, machine learning, IoT security