Supporting Both Range Queries and Frequency Estimation with Local Differential Privacy

Xiaolan Gu, Ming Li, Yang Cao, Li Xiong

Research output: Chapter in Book/Report/Conference proceedingConference contribution

14 Scopus citations

Abstract

Local Differential Privacy (LDP)provides provable privacy protection for data collection without the assumption of the trusted data server. Existing mechanisms that satisfy LDP or its variants either only consider aggregate queries from a group of users (e.g., frequency estimation)or individual queries for a single user (e.g., range queries). However, in complex real-world analytics applications, it is desirable to support both types of queries at the same time. In this paper, we tackle the challenge of privately answering range queries and providing frequency estimation at the same time with high utility. We develop a data perturbation mechanism, which is proved to satisfy local d-privacy (a generalized version of LDP with distance metric)and have optimal utility for the co-location query (a specific type of range query). Then, we utilize an inversion approach for frequency estimation using the perturbed data. We analyze the theoretical Mean Square Error (MSE)of this estimation method and show the relationship to another existing estimation method under LDP. The results on both synthetic and real-world location datasets validate the correctness of our theoretical analysis and show that the proposed mechanism has better utility for both range queries and frequency estimation than the state-of-The-Art mechanisms.

Original languageEnglish (US)
Title of host publication2019 IEEE Conference on Communications and Network Security, CNS 2019
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages124-132
Number of pages9
ISBN (Electronic)9781538671177
DOIs
StatePublished - Jun 2019
Externally publishedYes
Event2019 IEEE Conference on Communications and Network Security, CNS 2019 - Washington, United States
Duration: Jun 10 2019Jun 12 2019

Publication series

Name2019 IEEE Conference on Communications and Network Security, CNS 2019

Conference

Conference2019 IEEE Conference on Communications and Network Security, CNS 2019
Country/TerritoryUnited States
CityWashington
Period6/10/196/12/19

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Hardware and Architecture
  • Information Systems and Management
  • Safety, Risk, Reliability and Quality

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