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ICEB
2004

Privacy-Preserving Data Mining in Electronic Surveys

11 years 2 months ago
Privacy-Preserving Data Mining in Electronic Surveys
Electronic surveys are an important resource in data mining. However, how to protect respondents' data privacy during the survey is a challenge to the security and privacy community. In this paper, we develop a scheme to solve the problem of privacy-preserving data mining in electronic surveys. We propose a randomized response technique to collect the data from the respondents. We then demonstrate how to perform data mining computations on randomized data. Specifically, we apply our scheme to build a Naive Bayesian classifier from randomized data. Our experimental results indicate that accuracy of classification in our scheme, when private data is protected by randomization, is close to the accuracy of a classifier build from the same data with the total disclosure of private information. Finally, we develop a measure to quantify privacy achieved by our proposed scheme.
Justin Z. Zhan, Stan Matwin
Added 31 Oct 2010
Updated 31 Oct 2010
Type Conference
Year 2004
Where ICEB
Authors Justin Z. Zhan, Stan Matwin
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