Privacy-preserving human activity sensing: A survey

Yanni YANG*, Pengfei HU, Jiaxing SHEN, Haiming CHENG, Zhenlin AN, Xiulong LIU

*Corresponding author for this work

Research output: Journal PublicationsJournal Article (refereed)peer-review


With the prevalence of various sensors and smart devices in people's daily lives, numerous types of information are being sensed. While using such information provides critical and convenient services, we are gradually exposing every piece of our behavior and activities. Researchers are aware of the privacy risks and have been working on preserving privacy while sensing human activities. This survey reviews existing studies on privacy-preserving human activity sensing. We first introduce the sensors and captured private information related to human activities. We then propose a taxonomy to structure the methods for preserving private information from two aspects: individual and collaborative activity sensing. For each of the two aspects, the methods are classified into three levels: signal, algorithm, and system. Finally, we discuss the open challenges and provide future directions.

Original languageEnglish
Article number100204
JournalHigh-Confidence Computing
Issue number1
Early online date1 Mar 2024
Publication statusPublished - Mar 2024

Bibliographical note

Publisher Copyright:
© 2024 The Author(s)


  • Activity sensing algorithms
  • Human activity sensing
  • Human sensors
  • Privacy protection
  • Privacy-preserving sensing


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