This paper investigates the view update problem for XML views published from relational data. We consider XML views defined in terms of mappings directed by possibly recursive DTDs compressed into DAGs and stored in r...This paper investigates the view update problem for XML views published from relational data. We consider XML views defined in terms of mappings directed by possibly recursive DTDs compressed into DAGs and stored in relations. We provide new techniques to efficiently support XML view updates specified in terms of XPath expressions with recursion and complex filters. The interaction between XPath recursion and DAG compression of XML views makes the analysis of the XML view update problem rather intriguing. Furthermore, many issues are still open even for relational view updates, and need to be explored. In response to these, on the XML side we revise the notion of side effects and update semantics based on the semantics of XML views, and present efficient algorithms to translate XML updates to relational view updates. On the relational side, we propose a mild condition on SPJ views, and show that under this condition the analysis of deletions on relational views becomes PTIME while the insertion analysis is NP-complete. We develop an efficient algorithm to process relational view deletions, and a heuristic algorithm to handle view insertions. Finally, we present an experimental study to verify the effectiveness of our techniques.展开更多
In the era of big data,the conflict between data mining and data privacy protection is increasing day by day.Traditional information security focuses on protecting the security of attribute values without semantic ass...In the era of big data,the conflict between data mining and data privacy protection is increasing day by day.Traditional information security focuses on protecting the security of attribute values without semantic association.The data privacy of big data is mainly reflected in the effective use of data without exposing the user’s sensitive information.Considering the semantic association,reasonable security access for privacy protect is required.Semi-structured and self-descriptive XML(eXtensible Markup Language)has become a common form of data organization for database management in big data environments.Based on the semantic integration nature of XML data,this paper proposes a data access control model for individual users.Through the semantic dependency between data and the integration process from bottom to top,the global visual range of inverted XML structure is realized.Experimental results show that the model effectively protects the privacy and has high access efficiency.展开更多
基金Wenfei Fan is supported in part by EPSRC under Grants No.GR/S63205/01,No.GR/T27433/01,and No.EP/E029213/1.
文摘This paper investigates the view update problem for XML views published from relational data. We consider XML views defined in terms of mappings directed by possibly recursive DTDs compressed into DAGs and stored in relations. We provide new techniques to efficiently support XML view updates specified in terms of XPath expressions with recursion and complex filters. The interaction between XPath recursion and DAG compression of XML views makes the analysis of the XML view update problem rather intriguing. Furthermore, many issues are still open even for relational view updates, and need to be explored. In response to these, on the XML side we revise the notion of side effects and update semantics based on the semantics of XML views, and present efficient algorithms to translate XML updates to relational view updates. On the relational side, we propose a mild condition on SPJ views, and show that under this condition the analysis of deletions on relational views becomes PTIME while the insertion analysis is NP-complete. We develop an efficient algorithm to process relational view deletions, and a heuristic algorithm to handle view insertions. Finally, we present an experimental study to verify the effectiveness of our techniques.
基金This work was supported by Funding of Jiangsu Innovation Program for Graduate Education KYLX_0285,the National Natural Science Foundation of China(No.61602241)the Natural Science Foundation of Jiangsu Province(No.BK20150758)the pre-study fund of PLA University of Science and Technology.
文摘In the era of big data,the conflict between data mining and data privacy protection is increasing day by day.Traditional information security focuses on protecting the security of attribute values without semantic association.The data privacy of big data is mainly reflected in the effective use of data without exposing the user’s sensitive information.Considering the semantic association,reasonable security access for privacy protect is required.Semi-structured and self-descriptive XML(eXtensible Markup Language)has become a common form of data organization for database management in big data environments.Based on the semantic integration nature of XML data,this paper proposes a data access control model for individual users.Through the semantic dependency between data and the integration process from bottom to top,the global visual range of inverted XML structure is realized.Experimental results show that the model effectively protects the privacy and has high access efficiency.
