Understanding Database Reconstruction Attacks on Public Data
Loading...
No Access Until
Permanent Link(s)
Collections
Other Titles
Abstract
In 2020 the U.S. Census Bureau will conduct the Constitutionally mandated decennial Census of Population and Housing. Because a census involves collecting large amounts of private data under the promise of confidentiality, traditionally statistics are published only at high levels of aggregation. Published statistical tables are vulnerable to DRAs (database reconstruction attacks), in which the underlying microdata is recovered merely by finding a set of microdata that is consistent with the published statistical tabulations. A DRA can be performed by using the tables to create a set of mathematical constraints and then solving the resulting set of simultaneous equations. This article shows how such an attack can be addressed by adding noise to the published tabulations, so that the reconstruction no longer results in the original data.
Journal / Series
Volume & Issue
Description
Sponsorship
Date Issued
2018-01-01
Publisher
Keywords
Statistics; privacy; data
Location
Effective Date
Expiration Date
Sector
Employer
Union
Union Local
NAICS
Number of Workers
Committee Chair
Committee Co-Chair
Committee Member
Degree Discipline
Degree Name
Degree Level
Related Version
Published in ACMQueue, Vol. 16, No. 5 (September/October 2018): 28-53.
Related DOI
Related To
Related Part
Based on Related Item
Has Other Format(s)
Part of Related Item
Related To
https://queue.acm.org/detail.cfm?id=3295691