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The statistical security of a statistical database

Editor: Robert W. Taylor Authors:

J. F. Traub,

Y. Yemini,

H. WoźniakowskiAuthors Info & Claims

ACM Transactions on Database Systems (TODS), Volume 9, Issue 4

Pages 672 - 679

https://doi.org/10.1145/1994.383392

Published: 05 December 1984 Publication History

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Abstract

This note proposes a statistical perturbation scheme to protect a statistical database against compromise. The proposed scheme can handle the security of numerical as well as nonnumerical sensitive fields. Furthermore, knowledge of some records in a database does not help to compromise unknown records. We use Chebyshev's inequality to analyze the trade-offs among the magnitude of the perturbations, the error incurred by statistical queries, and the size of the query set to which they apply. We show that if the statistician is given absolute error guarantees, then a compromise is possible, but the cost is made exponential in the size of the database.

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Cited By

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Muralidhar KDomingo-Ferrer J(2023)Database Reconstruction Is Not So Easy and Is Different from ReidentificationJournal of Official Statistics10.2478/jos-2023-001739:3(381-398)Online publication date: 7-Sep-2023
https://doi.org/10.2478/jos-2023-0017
Xu HZhang N(2022)Implications of Data Anonymization on the Statistical Evidence of DisparityManagement Science10.1287/mnsc.2021.402868:4(2600-2618)Online publication date: 1-Apr-2022
https://dl.acm.org/doi/10.1287/mnsc.2021.4028
Zhang TLiu XWang JVictor Chan W(2022)A Novel Mixed Integer Programming Formulation for Data Perturbation2022 7th International Conference on Big Data Analytics (ICBDA)10.1109/ICBDA55095.2022.9760361(35-39)Online publication date: 4-Mar-2022
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Index Terms

The statistical security of a statistical database
1. Applied computing
  1. Physical sciences and engineering
    1. Mathematics and statistics
2. Information systems
  1. Data management systems
  2. Information systems applications
    1. Decision support systems
      1. Data analytics

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Published In

cover image ACM Transactions on Database Systems

ACM Transactions on Database Systems Volume 9, Issue 4

Dec. 1984

208 pages

ISSN:0362-5915

EISSN:1557-4644

DOI:10.1145/1994

Editor:
Robert W. Taylor
Digital Equipment Corporation, Bedford, MA

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 05 December 1984

Published in TODS Volume 9, Issue 4

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Muralidhar KDomingo-Ferrer J(2023)Database Reconstruction Is Not So Easy and Is Different from ReidentificationJournal of Official Statistics10.2478/jos-2023-001739:3(381-398)Online publication date: 7-Sep-2023
https://doi.org/10.2478/jos-2023-0017
Xu HZhang N(2022)Implications of Data Anonymization on the Statistical Evidence of DisparityManagement Science10.1287/mnsc.2021.402868:4(2600-2618)Online publication date: 1-Apr-2022
https://dl.acm.org/doi/10.1287/mnsc.2021.4028
Zhang TLiu XWang JVictor Chan W(2022)A Novel Mixed Integer Programming Formulation for Data Perturbation2022 7th International Conference on Big Data Analytics (ICBDA)10.1109/ICBDA55095.2022.9760361(35-39)Online publication date: 4-Mar-2022
https://doi.org/10.1109/ICBDA55095.2022.9760361
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Harikumar HRana SGupta SNguyen TKaimal RVenkatesh S(2021)Prescriptive analytics with differential privacyInternational Journal of Data Science and Analytics10.1007/s41060-021-00286-w13:2(123-138)Online publication date: 22-Sep-2021
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Gast NIoannidis SLoiseau PRoussillon B(2020)Linear Regression from Strategic Data SourcesACM Transactions on Economics and Computation10.1145/33914368:2(1-24)Online publication date: 13-May-2020
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Wang JChan W(2020)TPEGADP: improvement of EGADP based on topology potential2020 5th IEEE International Conference on Big Data Analytics (ICBDA)10.1109/ICBDA49040.2020.9101253(226-230)Online publication date: May-2020
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Baskerville RVaishnavi V(2020)A Novel Approach to Collectively Determine Cybersecurity Performance Benchmark DataDesign Science Research. Cases10.1007/978-3-030-46781-4_2(17-41)Online publication date: 24-Sep-2020
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Chu ALam BTiwari ASo M(2019)An Empirical Study of Applying Statistical Disclosure Control Methods to Public Health ResearchInternational Journal of Environmental Research and Public Health10.3390/ijerph1622451916:22(4519)Online publication date: 15-Nov-2019
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A security machanism for statistical database

Statistical relational tables for statistical database management

Revisiting the Security of Biometric Authentication Systems Against Statistical Attacks

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