计算机科学 ›› 2010, Vol. 37 ›› Issue (4): 146-.
• 软件工程与数据库技术 • 上一篇 下一篇
宋金玲,赵威,刘欣,黄立明,李金才,刘国华
出版日期:
发布日期:
基金资助:
SONG Jin-ling,ZHAO Wei,LIU Xin,HUANG Li-ming,LI Jin-cai,LIU Guo-hua
Online:
Published:
摘要: 发布寿匿名数据集可以起到有效保护隐私的目的,但如何保持寿匿名数据集与原始数据集的同步更新是一个亟待解决的问题。为了解决这个问题,在详细分析k-匿名数据集更新情况的基础上,给出了k-匿名数据集的增量更新算法:针对具体的更新操作,首先根据语义贴近度及元组映射等方法对更新元组在寿匿名数据集中进行定位,再对更新元组进行相应的更新操作。所提算法不仅保证了数据集的k-匿名约束性质,而且保证了k-匿名数据集与原始数据集的实时一致性。
关键词: k-匿名,增量更新,插入,删除,修改
Abstract: K-anonymity is an effective method to prevent linking attack and protect privacy. The main idea of k-anonymity is generalizing the values on a set of special attributes named ctuasi-identifier, so that gains a k-anonymized dataset in which the values of each tuple on quasi-identifier must repeat at least k occurrences. Although k-anonymized dataset guarantees privacy, the k-anonymized dataset needs to be updated constantly because the original dataset updates occasionally after a version of k-anonymized dataset has been existed. So, how to update the k-anonymized dataset as well as the original dataset becomes an urgent problem. To solve this problem, based on the detailed analysis to various update situations of the k-anonymized dataset, the increment update algorithms for the k-anonymized dataset were presented.
Key words: k-anonymity, Increment update, Insert, Delete, Modify
宋金玲,赵威,刘欣,黄立明,李金才,刘国华. k-匿名数据集的增量更新算法[J]. 计算机科学, 2010, 37(4): 146-. https://doi.org/
SONG Jin-ling,ZHAO Wei,LIU Xin,HUANG Li-ming,LI Jin-cai,LIU Guo-hua. Algorithm for Increment Update of k-Anonymized Dataset[J]. Computer Science, 2010, 37(4): 146-. https://doi.org/
0 / / 推荐
导出引用管理器 EndNote|Reference Manager|ProCite|BibTeX|RefWorks
链接本文: https://www.jsjkx.com/CN/
https://www.jsjkx.com/CN/Y2010/V37/I4/146
Cited