Abstract
Paper first analyzes the major technical database of existing privacy and privacy requirements in more sensitive attribute data released under the scenarios studied in the publishing process more sensitive data privacy issues, pointing out that a single individual more than the corresponding records and the corresponding personal data published anonymously in the privacy protection model number of key issues need to be addressed, including information disclosure risk measure, information loss measure and control the dynamic semantic tree, and induction, summed up the release of existing multi-attribute data privacy-sensitive technology characteristics.
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References
Litai, Y., Tang, C., Wu, J., Zhou, M.: Two clustering based on k-anonymity privacy protection. Jilin University (Information Science) (February 2009)
Han, J., Cen, T., Yu, H.: Data table k-anonymous study of the micro-clustering algorithm. Electronics (October 2008)
Li, J.I., Lv, Y., Zhao, W., Liu, G., Li, H.J.: Barrels of K-based anonymity multidimensional table incremental update algorithm. Yanshan University (May 2009)
Qi, R., Wang, K., Guo, X., Li, J., Tang, J., Liu, G.: Priority strategy based on the maximum Ye Zizi tree protection method of multi-sensitive properties. Yanshan University (May 2009)
Teng, J., Zhong, C.: Anonymous method based on data published privacy leaks Control Technologies. Guangxi Academy of Sciences (April 2009)
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Yali, H., Guoxing, P. (2011). The Research on Algorithm of Multi-sensitive Properties Privacy Based on Personal Anonymity. In: Lin, S., Huang, X. (eds) Advances in Computer Science, Environment, Ecoinformatics, and Education. CSEE 2011. Communications in Computer and Information Science, vol 215. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-23324-1_68
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DOI: https://doi.org/10.1007/978-3-642-23324-1_68
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-23323-4
Online ISBN: 978-3-642-23324-1
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