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Research on K-Anonymity for Privacy Preserving

Author: LiuJian
Tutor: LiuZuo
School: Donghua University
Course: Computer Software and Theory
Keywords: K-anonymity Entropy Data Mining Privacy Medical database
CLC: TP309
Type: Master's thesis
Year: 2010
Downloads: 381
Quote: 2
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Abstract


K-anonymity is important privacy information security information sharing, can effectively prevent the sharing of data processing after K-anonymity Links attacks, to avoid the disclosure of private information. First of all, according to the different objects of the protection of privacy in information sharing, respectively, for raw data privacy protection and the protection of privacy for data mining knowledge analyzed. K-anonymity privacy protection model research background, and implementation techniques, and K-anonymity model described by examples. Secondly, a series of research results in the previous study, the K-anonymity technology to achieve algorithm global generalization algorithm and local generalization algorithms, respectively, a comparative analysis of some of the more classic performance of the algorithm, analyze the advantages and shortcomings of the existing K-anonymity algorithm. K-anonymity and privacy protection model may be affected by a variety of attacks carried out theoretical study, this paper presents a K-anonymity privacy protection model five attacks described by way of example, and put forward a series of solutions, In order to prevent attacks against K-anonymity privacy model provide strong protection. Then, the analysis of the K-anonymity privacy protection model main method concealment and generalization, and study the accuracy of different generalization approach for anonymizing data affect differences. Introduces the idea of ??entropy K-anonymity privacy model proposed K-anonymity privacy protection entropy-based classification algorithm Entropy algorithm. Through experiments verify the Entropy algorithm performance, and Entropy algorithm time complexity analysis as well as the accuracy of anonymized data analysis based on experimental data, experiments show that the algorithm in the previous algorithm based on the improvement . Finally, under the same experimental environment, experimental results of this paper, Entropy algorithm previously proposed global generalization algorithm Basic Incognito algorithm performance. Entropy algorithm according to the results of the experimental data, the performance of the algorithm with the Basic Incognito comparative analysis, including the time complexity of the analysis, and the accuracy of analysis. The analysis results show that the Entropy algorithm in terms of running time than Basic for the Incognito algorithm requires a longer time, but Entropy algorithm is very good to ensure the anonymized data accuracy, at the same time ensure that the shared data to meet K-anonymity requirements, effective the reference to the use of anonymous data value.

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CLC: > Industrial Technology > Automation technology,computer technology > Computing technology,computer technology > General issues > Security and confidentiality
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