Multidimensional data provides enormous opportunities in a variety of applications. Recent research has indicated the failure of existing sanitization techniques （e.g., k-anonymity） to provide rigorous privacy guara...Multidimensional data provides enormous opportunities in a variety of applications. Recent research has indicated the failure of existing sanitization techniques （e.g., k-anonymity） to provide rigorous privacy guarantees. Privacy- preserving multidimensional data publishing currently lacks a solid theoretical foundation. It is urgent to develop new techniques with provable privacy guarantees, e-Differential privacy is the only method that can provide such guarantees. In this paper, we propose a multidimensional data publishing scheme that ensures c-differential privacy while providing accurate results for query processing. The proposed solution applies nonstandard wavelet transforms on the raw multidimensional data and adds noise to guarantee c-differential privacy. Then, the scheme processes arbitrarily queries directly in the noisy wavelet- coefficient synopses of relational tables and expands the noisy wavelet coefficients back into noisy relational tuples until the end result of the query. Moreover, experimental results demonstrate the high accuracy and effectiveness of our approach.展开更多
Most efficient indeces and query techniques over XML （extensible markup language） data are based on a certain labeling scheme, which can quickly determine ancestor-descendant and parent-child relationship between tw...Most efficient indeces and query techniques over XML （extensible markup language） data are based on a certain labeling scheme, which can quickly determine ancestor-descendant and parent-child relationship between two nodes. The current basic labeling schemes such as containment scheme and prefix scheme cannot avoid re- labeling when XML documents are updated. After analyzing the essence of existing dynamic XML labels such as compact dynamic binary string （CDBS） and vector encoding, this paper gives a common unifying framework for the numeric-based generalized dynamic label, which can be implemented into a variety of dynamic labels according to the different user-defined value comparison methods. This paper also proposes a novel dynamic labeling scheme called radical sign label. Extensive experiments show that the radical sign label performs well for the initialization, insertion and query operations, and especially for skewed insertion where the storage cost of the radical sign label is better than that of former methods.展开更多
基金the National Basic Research Program of China under Grant 2013CB338004,Doctoral Program of Higher Education of China under Grant No.20120073120034,National Natural Science Foundation of China under Grants No.61070204,61101108,and National S&T Major Program under Grant No.2011ZX03002-005-01
文摘Multidimensional data provides enormous opportunities in a variety of applications. Recent research has indicated the failure of existing sanitization techniques （e.g., k-anonymity） to provide rigorous privacy guarantees. Privacy- preserving multidimensional data publishing currently lacks a solid theoretical foundation. It is urgent to develop new techniques with provable privacy guarantees, e-Differential privacy is the only method that can provide such guarantees. In this paper, we propose a multidimensional data publishing scheme that ensures c-differential privacy while providing accurate results for query processing. The proposed solution applies nonstandard wavelet transforms on the raw multidimensional data and adds noise to guarantee c-differential privacy. Then, the scheme processes arbitrarily queries directly in the noisy wavelet- coefficient synopses of relational tables and expands the noisy wavelet coefficients back into noisy relational tuples until the end result of the query. Moreover, experimental results demonstrate the high accuracy and effectiveness of our approach.
基金the National Major Projects on Science and Technology(No.2010ZX01042-002-003-004)the National Basic Research Program (973) of China(No.2010CB328106)+2 种基金the National Natural Science Foundation of China(No. 61170085)the Program for New Century Excellent Talents in China(No.NCET-10-0388)the Shanghai Leading Academic Discipline Project(No.B412)
文摘Most efficient indeces and query techniques over XML （extensible markup language） data are based on a certain labeling scheme, which can quickly determine ancestor-descendant and parent-child relationship between two nodes. The current basic labeling schemes such as containment scheme and prefix scheme cannot avoid re- labeling when XML documents are updated. After analyzing the essence of existing dynamic XML labels such as compact dynamic binary string （CDBS） and vector encoding, this paper gives a common unifying framework for the numeric-based generalized dynamic label, which can be implemented into a variety of dynamic labels according to the different user-defined value comparison methods. This paper also proposes a novel dynamic labeling scheme called radical sign label. Extensive experiments show that the radical sign label performs well for the initialization, insertion and query operations, and especially for skewed insertion where the storage cost of the radical sign label is better than that of former methods.
