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Freedom of Privacy: Anonymous Data Collection with Respondent-Defined Privacy Protection

Department of Accounting and Finance, Kutztown University, Kutztown, Pennsylvania, 19530
Department of Operations and Information Management, University of Connecticut, Storrs, Connecticut 06269
Department of Operations and Information Management, University of Connecticut, Storrs, Connecticut 06269
rkumar{at}kutztown.edu
rgopal{at}business.uconn.edu
rgarfinkel{at}business.uconn.edu

The massive amount of sensitive survey data about individuals that agencies collect and share through the Internet is causing a great deal of privacy concerns. These concerns may discourage individuals from revealing their sensitive information. Existing data collection techniques have serious downsides in terms of both efficiency and the levels of protection they offer against various realizations of threats. Moreover, they do not provide any flexibility to the users to be able to specify acceptable levels of privacy protection before deciding whether to participate in the surveys. In this paper, we propose a two-pronged privacy protection model corresponding to these two privacy concerns: these are a new efficient anonymity preserving data collection technique and a method to incorporate heterogeneous privacy constraints. Together, they help preserve the privacy of respondents both during and after data collection.

Key words: data collection; anonymity; privacy; information security
History: received March 2008; revised June 2009; accepted September 2009.