Satisfying privacy requirements: one step before anonymization

Sun, Xiaoxun and Wang, Hua and Li, Jiuyong (2010) Satisfying privacy requirements: one step before anonymization. In: PAKDD 2010: 14th Pacific-Asia Conference on Knowledge Discovery and Data Mining , 21-24 Jun 2010, Hyderabad, India.

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Abstract

In this paper, we study a problem of privacy protection in large survey rating data. The rating data usually contains both ratings of sensitive and non-sensitive issues, and the ratings of sensitive issues include personal information. Even when survey participants do not reveal any of their ratings, their survey records are potentially identifiable by using information from other public sources. We propose a new (k, , l)- anonymity model, in which each record is required to be similar with at least k−l others based on the non-sensitive ratings, where the similarity is controlled by , and the standard deviation of sensitive ratings is at least l. We study an interesting yet nontrivial satisfaction problem of the (k, , l)-anonymity, which is to decide whether a survey rating data set satisfies the privacy requirements given by users. We develop a slice technique for the satisfaction problem and the experimental results show that the slicing technique is fast, scalable and much more efficient in terms of execution time than the heuristic pairwise method.


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Item Type: Conference or Workshop Item (Commonwealth Reporting Category E) (Paper)
Refereed: Yes
Item Status: Live Archive
Additional Information: Series title: Lecture Notes in Computer Science v. 6118 Author version not held. Published version cannot be displayed.
Depositing User: Dr Hua Wang
Faculty / Department / School: Historic - Faculty of Sciences - Department of Maths and Computing
Date Deposited: 23 Sep 2010 03:19
Last Modified: 10 Sep 2014 23:23
Uncontrolled Keywords: privacy protection; survey rating data; anonymization; data sets; execution time; one step; personal information; privacy requirements; problem of privacy; satisfaction problem; standard deviation
Fields of Research (FOR2008): 08 Information and Computing Sciences > 0804 Data Format > 080402 Data Encryption
17 Psychology and Cognitive Sciences > 1701 Psychology > 170113 Social and Community Psychology
08 Information and Computing Sciences > 0803 Computer Software > 080303 Computer System Security
Socio-Economic Objective (SEO2008): E Expanding Knowledge > 97 Expanding Knowledge > 970108 Expanding Knowledge in the Information and Computing Sciences
Identification Number or DOI: doi: 10.1007/978-3-642-13657-3_21
URI: http://eprints.usq.edu.au/id/eprint/8486

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