A Comprehensive Survey on Local Differential Privacy toward Data Statistics and Analysis

• Published in: Sensors (Basel, Switzerland) Vol. 20; no. 24; p. 7030
• Main Authors: Wang, Teng, Zhang, Xuefeng, Feng, Jingyu, Yang, Xinyu
• Format: Journal Article
• Language: English
• Published: Switzerland MDPI AG 08.12.2020; MDPI
• Subjects: Algorithms; applications; Big Data; data statistics and analysis; enabling mechanisms; Hypothesis testing; Internet of Things; local differential privacy; Machine learning; Privacy; Probability; Recommender systems; Review; enabling mechanisms; data statistics and analysis; local differential privacy; applications

Collecting and analyzing massive data generated from smart devices have become increasingly pervasive in crowdsensing, which are the building blocks for data-driven decision-making. However, extensive statistics and analysis of such data will seriously threaten the privacy of participating users. Lo...