Optimal Differentially Private Mechanisms for Randomised Response

Optimal Differentially Private Mechanisms for Randomised Response

We examine a generalised randomised response (RR) technique in the context of differential privacy and examine the optimality of such mechanisms. Strict and relaxed differential privacy are considered for binary outputs. By examining the error of a statistical estimator, we present closed solutions...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:IEEE transactions on information forensics and security 2017-11, Vol.12 (11), p.2726-2735
Hauptverfasser: Holohan, Naoise, Leith, Douglas J., Mason, Oliver
Format: Artikel
Sprache:eng
Schlagworte:
Computational modeling
Data privacy
differential privacy
local privacy
Mathematical model
Maximum likelihood estimation
optimality
Optimization
Privacy
Randomization
Randomized response
Sociology
Online-Zugang:Volltext bestellen
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
Beschreibung
Zusammenfassung:We examine a generalised randomised response (RR) technique in the context of differential privacy and examine the optimality of such mechanisms. Strict and relaxed differential privacy are considered for binary outputs. By examining the error of a statistical estimator, we present closed solutions for the optimal mechanism(s) in both cases. The optimal mechanism is also given for the specific case of the original RR technique as introduced by Warner in 1965.
ISSN:1556-6013
1556-6021
DOI:10.1109/TIFS.2017.2718487