Privacy Protection Based on Packet Filtering for Home Internet-of-Things

Beibei Cheng, Yiming Zhu, Yuxuan Chen, Xiaodan Gu, Kai Dong

Abstract: The development of home internet of things (H-IoT) devices brings convenience but poses significant privacy and security risks. Existing research minimizes data uploaded to the cloud but fails to process data locally, resulting in a trade-off between privacy and functionality. In this paper, we propose a privacy-preserving method that identifies and processes sensitive data sent from H-IoT devices at the edge side, ensuring functionality while preserving privacy. Our method applies different identification strategies to packets with different features, making it applicable to most H-IoT devices and scenarios. We validate our approach through experiments on a prototype system that monitors multiple cameras, demonstrating its effectiveness in preserving privacy while maintaining functionality.