Title
The Role of Interactivity in Local Differential Privacy
Abstract
We study the power of interactivity in local differential privacy. First, we focus on the difference between fully interactive and sequentially interactive protocols. Sequentially interactive protocols may query users adaptively in sequence, but they cannot return to previously queried users. The vast majority of existing lower bounds for local differential privacy apply only to sequentially interactive protocols, and before this paper it was not known whether fully interactive protocols were more powerful. We resolve this question. First, we classify locally private protocols by their compositionality, the multiplicative factor by which the sum of a protocol's single-round privacy parameters exceeds its overall privacy guarantee. We then show how to efficiently transform any fully interactive compositional protocol into an equivalent sequentially interactive protocol with a blowup in sample complexity linear in this compositionality. Next, we show that our reduction is tight by exhibiting a family of problems such that any sequentially interactive protocol requires this blowup in sample complexity over a fully interactive compositional protocol. We then turn our attention to hypothesis testing problems. We show that for a large class of compound hypothesis testing problems - which include all simple hypothesis testing problems as a special case - a simple noninteractive test is optimal among the class of all (possibly fully interactive) tests.
Year
DOI
Venue
2019
10.1109/FOCS.2019.00015
2019 IEEE 60th Annual Symposium on Foundations of Computer Science (FOCS)
Keywords
Field
DocType
differential privacy,local differential privacy,interaction
Principle of compositionality,Interactivity,Multiplicative function,Differential privacy,Theoretical computer science,Tilde,Artificial intelligence,Sample complexity,Mathematics,Statistical hypothesis testing,Machine learning,Special case
Journal
Volume
ISSN
ISBN
abs/1904.03564
1523-8288
978-1-7281-4953-0
Citations 
PageRank 
References 
1
0.34
8
Authors
4
Name
Order
Citations
PageRank
Joseph, Matthew1493.77
Jieming Mao2549.19
Seth Neel3527.86
Aaron Roth41937110.48