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

Kumar, Rajeev, Ram Gopal, and Robert Garfinkel. "Freedom of Privacy:Anonymous Data Collection with Respondent-Defined Privacy Protection." INFORMS Journal on Computing 22, no. 3 (Summer 2010): 471-481.

This article explores how various organizations collecting survey data on individuals are creating wide-spread privacy concerns. The authors illustrate how existing methods for data collection are lacking in efficiency and privacy. They propose two ways of handling data that will respond to these concerns.

The article offers several examples of how customers’ privacy is breached, including various ways that data collected from customers is matched with personally identifiable information as well as hackers obtaining the information.

The authors two suggestions for privacy collection involve: allowing individuals to create their own privacy levels and then base data collection on those profiles and the utilization of a new anonymous data collection technique whereby the data collected can’t be matched with the users’ personally identifiable information. The first approach which allows individuals the ability to choose their own privacy levels is a straightforward approach that ensures privacy throughout the lifecycle of the transaction. The second approach, the use of the authors’ anonymous data collection technique called KGG Data Collection, is a complex data collection system whereby users send and receive encrypted and decrypted messages involving their data. The paper attempts to solve the problem of privacy issues, created by agencies who collect survey data, by the creation of a new system of data collection described in this article by the authors.

The authors present a sound, well-researched, and detailed account of their data collection techniques, as well as a literature review comparing and contrasting previous techniques. The article only uses previous literature to provide evidence supporting their hypotheses and their software development. However, because they are developers, they are able to create a new system themselves instead of just discussing the possibilities of what could be done.

The article is somewhat relevant to my research project because it presents a unique approach to solving the problem of online privacy which is developed by the authors themselves. They detail their development of their anonymous data collection technique using scientific math and algorithms, probably written for an audience of engineers and software developers. Their technique seems somewhat complex and cumbersome, but it does provide a solid way for online users to ensure their data remains private, which seems to be at a premium these days.