Privacy-preserving human activity sensing:A survey  

作　　者：Yanni Yang Pengfei Hu Jiaxing Shen Haiming Cheng Zhenlin An Xiulong Liu 

机构地区：[1]School of Computer Science and Technology,Shandong University,Qingdao 266237,China [2]Department of Computing and Decision Sciences,Lingnan University,Hong Kong,China [3]Department of Computing,The Hong Kong Polytechnic University,Hong Kong,China [4]Department of Computer Science,Princeton University,NJ 08544,USA [5]College of Intelligence and Computing,Tianjin University,Tianjin 300350,China

出　　处：《High-Confidence Computing》2024年第1期108-117,共10页高置信计算（英文）

基　　金：supported by the National Key Research and Development Program of China(2021YFB3100400);National Natural Science Foundation of China(62302274,62202276 and 62232010);Shandong Science Fund for Excellent Young Scholars,China(2022HWYQ-038);Natural Science Foundation of Shandong,China(ZR2023QF113);financial support of Lingnan University(LU),China(DB23A4);Lam Woo Research Fund at LU,China(871236)。

摘　　要：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.

关 键 词：Human activity sensing Privacy-preserving sensing Activity sensing algorithms Human sensors Privacy protection 

分 类 号：TP309[自动化与计算机技术—计算机系统结构]