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Statistical Databases

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Encyclopedia of Cryptography and Security

Synonyms

Multidimensional databases; Online analytical processing

Related Concepts

ε-Privacy; Data Cube; Inference Control

Definition

A statistical database (SDB) system is a database system that enables its users to retrieve only aggregate statistics (e.g., sample mean and count) for a subset of the entities represented in the database.

Background

As a statistical database may contain sensitive individual information, such as salary and health records, generally, users are only allowed to retrieve aggregate statistics for a subset of the entities represented in the databases. Common aggregate query operators in SQL include SUM, COUNT, MAX, MIN, and AVERAGE, though more sophisticated statistical measures may also be supported by some database systems.

Statistical databases pose unique security concerns, which have been the focus of much research. However, the key security challenge is that of ensuring that no user is able to infer private information with respect to a privacy...

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Recommended Reading

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Author information

Authors and Affiliations

  1. Department of Management Science and Information Systems, CIMIC, Rutgers, The State University of New Jersey, 1 Washington Park, 07102, Newark, NJ, USA

    Nabil Adam (Professor), Haibing Lu & Jaideep Vaidya (Professor)

  2. CIMIC, Rutgers, The State University of New Jersey, 1 Washington Park, 07102, Newark, NJ, USA

    Basit Shafiq (Professor)

Authors
  1. Nabil Adam
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  2. Haibing Lu
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  3. Jaideep Vaidya
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  4. Basit Shafiq
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Editor information

Editors and Affiliations

  1. Department of Mathematics and Computing Science, Eindhoven University of Technology, 5600 MB, Eindhoven, The Netherlands

    Henk C. A. van Tilborg

  2. Center for Secure Information Systems, George Mason University, Fairfax, VA, 22030-4422, USA

    Sushil Jajodia

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Adam, N., Lu, H., Vaidya, J., Shafiq, B. (2011). Statistical Databases. In: van Tilborg, H.C.A., Jajodia, S. (eds) Encyclopedia of Cryptography and Security. Springer, Boston, MA. https://doi.org/10.1007/978-1-4419-5906-5_767

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