Hiding in plain sight: Anonymity and privacy preserving mechanisms for data collection and collaboration
Date of Completion
January 2009
Keywords
Business Administration, Management|Information Technology|Information Science
Degree
Ph.D.
Abstract
This dissertation contributes to the society by providing mechanisms that can potentially increase the availability of valuable personal level information without sacrificing the privacy of citizens. We consider two settings by which personal level data can be made available to its users such as researchers, who then may use it for the benefit of the society. These two methods are: (1) direct collection of data from the respondent via a survey, or (2) data obtained from an agency. Both processes create different types of risk to the respondents whose data is being used, and these risks are analyzed in the two essays of the dissertation. The first is a survey setting, and our approach provides an improved level of privacy protection to the respondents. Data users in the second setting obtain their data via a “free market.” In this setting, we not only provide a more enhanced privacy protection to individuals than the ones that exist in the privacy preserving data sharing literature, but also provide “appropriate compensation” to the respondents in the process. This compensation-based incentive mechanism can by itself potentially increase the availability of personal level information. The market is also designed to satisfy diverse “data quality” related demands of information users who act as buyers of the market. Even though these two settings have the same broad objective, they are analyzed separately in different essays. These essays can even be read independently as two different research articles.^
Recommended Citation
Kumar, Rajeev, "Hiding in plain sight: Anonymity and privacy preserving mechanisms for data collection and collaboration" (2009). Doctoral Dissertations. AAI3391696.
https://digitalcommons.lib.uconn.edu/dissertations/AAI3391696