Security problems on inference control for SUM, MAX, and MIN queries
Journal of the ACM (JACM)
Theory of linear and integer programming
Theory of linear and integer programming
A graph theoretic approach to statistical data security
SIAM Journal on Computing
Security-control methods for statistical databases: a comparative study
ACM Computing Surveys (CSUR)
A universal-scheme approach to statistical databases containing homogeneous summary tables
ACM Transactions on Database Systems (TODS)
PODS '00 Proceedings of the nineteenth ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
A Linear Algorithm for Finding the Invariant Edges of an Edge-Weighted Graph
SIAM Journal on Computing
On the Data Model and Access Method of Summary Data Management
IEEE Transactions on Knowledge and Data Engineering
Query Evaluability in Statistical Databases
IEEE Transactions on Knowledge and Data Engineering
ICDT '03 Proceedings of the 9th International Conference on Database Theory
Cardinality-Based Inference Control in Sum-Only Data Cubes
ESORICS '02 Proceedings of the 7th European Symposium on Research in Computer Security
Privacy in multidimensional databases
Multidimensional databases
Cardinality-based inference control in OLAP systems: an information theoretic approach
Proceedings of the 7th ACM international workshop on Data warehousing and OLAP
Cardinality-based inference control in data cubes
Journal of Computer Security
Theory of Relational Databases
Theory of Relational Databases
A model of summary data and its applications in statistical databases
SSDBM'1988 Proceedings of the 4th international conference on Statistical and Scientific Database Management
Minimal invariant sets in a vertex-weighted graph
Theoretical Computer Science
An analytical approach to the inference of summary data of additive type
Theoretical Computer Science
A dubiety-determining based model for database cumulated anomaly intrusion
Proceedings of the 2nd international conference on Scalable information systems
A Bayesian approach for on-line max and min auditing
PAIS '08 Proceedings of the 2008 international workshop on Privacy and anonymity in information society
A Probabilistic Framework for Building Privacy-Preserving Synopses of Multi-dimensional Data
SSDBM '08 Proceedings of the 20th international conference on Scientific and Statistical Database Management
A Robust Sampling-Based Framework for Privacy Preserving OLAP
DaWaK '08 Proceedings of the 10th international conference on Data Warehousing and Knowledge Discovery
Secure aggregation in a publish-subscribe system
Proceedings of the 7th ACM workshop on Privacy in the electronic society
An efficient online auditing approach to limit private data disclosure
Proceedings of the 12th International Conference on Extending Database Technology: Advances in Database Technology
A Bayesian model for disclosure control in statistical databases
Data & Knowledge Engineering
A Bayesian approach for on-line max auditing of dynamic statistical databases
Proceedings of the 2009 EDBT/ICDT Workshops
Journal of Computer and System Sciences
Statistical analysis for comparison of the key representation database with the original database
International Journal of Business Information Systems
Anonymity meets game theory: secure data integration with malicious participants
The VLDB Journal — The International Journal on Very Large Data Bases
A bayesian approach for on-line sum/count/max/min auditing on boolean data
PSD'12 Proceedings of the 2012 international conference on Privacy in Statistical Databases
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In response to queries asked to a statistical database, the query system should avoid releasing summary statistics that could lead to the disclosure of confidential individual data. Attacks to the security of a statistical database may be direct or indirect and, in order to repel them, the query system should audit queries by controlling the amount of information released by their responses. This paper focuses on sum-queries with a response variable of nonnegative real type and proposes a compact representation of answered sum-queries, called an information model in “normal form,” which allows the query system to decide whether the value of a new sum-query can or cannot be safely answered. If it cannot, then the query system will issue the range of feasible values of the new sum-query consistent with previously answered sum-queries. Both the management of the information model and the answering procedure require solving linear-programming problems and, since standard linear-programming algorithms are not polynomially bounded (despite their good performances in practice), effective procedures that make a parsimonious use of them are stated for the general case. Moreover, in the special case that the information model is “graphical.” It is shown that the answering procedure can be implemented in polynomial time.