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High Performance Datafly based Anonymity Algorithm and Its L-Diversity

High Performance Datafly based Anonymity Algorithm and Its L-Diversity

Zhi-ting Yu, Quan Qian, Chun-Yuan Lin, Che-Lun Hung
Copyright: © 2015 |Volume: 7 |Issue: 3 |Pages: 16
ISSN: 1938-0259|EISSN: 1938-0267|EISBN13: 9781466676671|DOI: 10.4018/IJGHPC.2015070106
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MLA

Yu, Zhi-ting, et al. "High Performance Datafly based Anonymity Algorithm and Its L-Diversity." IJGHPC vol.7, no.3 2015: pp.85-100. http://doi.org/10.4018/IJGHPC.2015070106

APA

Yu, Z., Qian, Q., Lin, C., & Hung, C. (2015). High Performance Datafly based Anonymity Algorithm and Its L-Diversity. International Journal of Grid and High Performance Computing (IJGHPC), 7(3), 85-100. http://doi.org/10.4018/IJGHPC.2015070106

Chicago

Yu, Zhi-ting, et al. "High Performance Datafly based Anonymity Algorithm and Its L-Diversity," International Journal of Grid and High Performance Computing (IJGHPC) 7, no.3: 85-100. http://doi.org/10.4018/IJGHPC.2015070106

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Abstract

Data anonymity, as an effective privacy protection method, has been widely used in real applications. High performance data anonymity algorithm is especially attractive for those massive data applications. In this paper, the authors propose a novel and efficient Datafly based data anonymity (Divide-Datafly) algorithm and the experimental results show that the proposed algorithm is not only more efficient than Datafly and Incognito, but also information loss less than KACA. Moreover, in order to improve the security of anonymous data, L-Divide-Datafly is presented that it combines Divide-Datafly and efficient distance based clustering. Experimental results show that L-Divide-Datafly achieves great performance both in execution time and Information loss.

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