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Towards an anti-inference (K, l)-anonymity model with value association rules
Li, Zude ; Zhan, Guoqiang ; Ye, Xiaojun
2010-05-07 ; 2010-05-07
会议名称DATABASE AND EXPERT SYSTEMS APPLICATIONS, PROCEEDINGS ; 17th International Conference on Database and Expert Systems Applications ; Cracow, POLAND ; Web of Science ; INSPEC
关键词K-ANONYMITY PRIVACY Computer Science, Theory & Methods
中文摘要As a privacy-preserving microdata publication model, K-Anonymity has some application limits, such as (1) it cannot satisfy the individual-defined k mechanism requirement, and (2) it is attached with a certain extent potential privacy disclosure risk on published microdata, i.e. existing high-probability inference violations under some prior knowledge on k-anonymized microdata that can surely result in personal private information disclosure. We propose the (k, l)-anonymity model with data generalization approach to support more flexible and anti-inference k-anonymization on a tabular microdata, where k indicates the anonymization level of an identifying attribute cluster and l refers to the diversity level of a sensitive attribute cluster on a record. Within the model, k and l are designed on each record and they can be defined subjectively by the corresponding individual. Beside, the model can prevent two kinds of inference attacks for microdata publication, (1) inferring identifying attributes values when their value domains are known; (2) inferring sensitive attributes values with respect to some value associations in the microdata. Further, we propose an algorithm to describe the k-anonymization process in the model. Finally, we take a scenario to illustrate its feasibility, flexibility, and generality.
会议录出版者SPRINGER-VERLAG BERLIN ; BERLIN ; HEIDELBERGER PLATZ 3, D-14197 BERLIN, GERMANY
语种英语 ; 英语
内容类型会议论文
源URL[http://hdl.handle.net/123456789/16979]  
专题清华大学
推荐引用方式
GB/T 7714
Li, Zude,Zhan, Guoqiang,Ye, Xiaojun. Towards an anti-inference (K, l)-anonymity model with value association rules[C]. 见:DATABASE AND EXPERT SYSTEMS APPLICATIONS, PROCEEDINGS, 17th International Conference on Database and Expert Systems Applications, Cracow, POLAND, Web of Science, INSPEC.
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