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A State Decision Tree based Backtracking Algorithm for Multi-Sensitive Attribute Privacy Preserving

Yanchao Zhang, Qing Liu, JunJun Cheng and JiJia Yang
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Yanchao Zhang: Institute of ICT Security Research, China Academy of Information and Communications Technology, Beijing, China
Qing Liu: Institute of ICT Security Research, China Academy of Information and Communications Technology, Beijing, China
JunJun Cheng: China Information Technology Security Evaluation Center, Beijing, China
JiJia Yang: Institute of ICT Security Research, China Academy of Information and Communications Technology, Beijing, China

International Journal of Interdisciplinary Telecommunications and Networking (IJITN), 2016, vol. 8, issue 2, 1-11

Abstract: Beyond l-diversity model, an algorithm (l-BDT) based on state decision tree is proposed in this paper, which aims at protecting multi-sensitive attributes from being attacked. The algorithm considers the whole situations in equivalence partitioning for the first, prunes the decision tree according to some conditions for the second, and screens out the method with the least information loss of equivalence partitioning for the last. The analysis and experiments show that the l-BDT algorithm has the best performance in controlling the information loss. It can be ensured that the published data is the most closed towards the original data, so as to ensure that the published data is as useful as possible.

Date: 2016
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