期刊名称：International Journal of Innovative Research in Science, Engineering and Technology
印刷版ISSN：2347-6710
电子版ISSN：2319-8753
出版年度：2015
卷号：4
期号：8
页码：6888
DOI：10.15680/IJIRSET.2015.0408177
出版社：S&S Publications
摘要：Micro data refers to series of records, each record with information on an individual unit like a patientor an organization. Access Control Mechanisms (ACM) protects the sensitive information from unauthorized users.Even authorized users may misuse the data to reveal the privacy of individuals to whom the data refers to. PrivacyProtection Mechanism (PPM) anonymize the relational data to prevent identity and attribute disclosure. It is achievedby generalization or suppression. Role-based access control gives users the permissions to access the data based ontheir roles. The access control policies define selection predicates available to roles while the privacy requirement isto satisfy the k-anonymity or l-diversity. Imprecision bound constraint is assigned for each selection predicate. TopDown Selection Mondrian (TDSM) algorithm is used for query workload-based anonymization. The Top DownSelection Mondrian (TDSM) algorithm is constructed using greedy heuristics and kd-tree model. Query cuts areselected with minimum bounds in Top-Down Heuristic 1 algorithm (TDH1). The query bounds are updated as thepartitions are added to the output in Top-Down Heuristic 2 algorithm (TDH2). The cost of reduced precision in thequery results is used in Top-Down Heuristic 3 algorithm (TDH3). Repartitioning algorithm is used to reduce the totalimprecision for the queries. The privacy preserved access control framework is enhanced to provide incrementalmining features using R+-tree. Data insert, delete and update operations are associated with the partitionmanagement mechanism.
关键词：Personal health records; cloud computing; data privacy; fine-grained access control; attribute- based;encryption
