Position Paper: Differential Privacy with Information Flow Control
Paper i proceeding, 2011

We investigate the integration of two approaches to information security: information flow analysis, in which the dependence between secret inputs and public outputs is tracked through a program, and differential privacy, in which a weak dependence between input and output is permitted but provided only through a relatively small set of known differentially private primitives. We find that information flow for differentially private observations is no harder than dependency tracking. Differential privacy's strong guarantees allow for efficient and accurate dynamic tracking of information flow, allowing the use of existing technology to extend and improve the state of the art for the analysis of differentially private computations.

dependency analysis

privacy

information flow

information security

Författare

Arnar Birgisson

Chalmers, Data- och informationsteknik, Programvaruteknik

Martín Abadi

Microsoft Research

Frank McSherry

Microsoft Research

Proceedings of ACM SIGPLAN Sixth Workshop on Programming Languages and Analysis for Security

2

Styrkeområden

Informations- och kommunikationsteknik

Ämneskategorier

Programvaruteknik

Datavetenskap (datalogi)

DOI

10.1145/2166956.2166958

ISBN

978-145030830-4

Mer information

Senast uppdaterat

2018-09-06