Paper Info
Title
Decoupled Data for Privacy Preserving Record Linkage with Error Management
Abstract
Data from social networks are an excellent source of information for studying human behaviors and interactions. Typically, when analyzing such data, the default mode of access is de-identified data, which provides a level of privacy protection. However, due to its inability to link to other data, de-identified data has limitations with regard to answering broad and critically important questions about our complex society. In this paper, we (1) investigate the properties of information related to privacy, and (2) present a novel model of data access, decoupled data access, for studying personal data using these properties. Decoupling refers to separating out the identifying information from the sensitive data that needs protection. We assert that decoupled data access can provide flexible record linkage with error management while still providing the same level of privacy protection as de-identified data.
Year
DOI
Venue
2011
10.1109/PASSAT/SocialCom.2011.97
SocialCom/PASSAT
Keywords
Field
DocType
computational social science,error management,data privacy,privacy preserving record linkage,social network,decoupled data,data analysis,decoupled data access model,de-identified data,behavioural sciences computing,human behavior,human interaction,social networking (online),record linkage,privacy protection,couplings,data model,social science,data models,data access,protocols,sensitivity,security,security protocol,privacy
Record linkage,Data modeling,Data quality,System of record,Computer science,Computer security,Human behavior,Information privacy,Data access,Data efficiency
Conference
ISBN
Citations 
PageRank 
978-1-4577-1931-8
1
0.36
References 
Authors
5
2
Name
Order
Citations
PageRank
Hye-Chung Kum111412.99
Stanley C. Ahalt243554.14