ACM SIGMOD Anthology ACM SIGMOD dblp.uni-trier.de

Security-Control Methods for Statistical Databases: A Comparative Study.

Nabil R. Adam, John C. Wortmann: Security-Control Methods for Statistical Databases: A Comparative Study. ACM Comput. Surv. 21(4): 515-556(1989)
@article{DBLP:journals/csur/AdamW89,
  author    = {Nabil R. Adam and
               John C. Wortmann},
  title     = {Security-Control Methods for Statistical Databases: A Comparative
               Study},
  journal   = {ACM Comput. Surv.},
  volume    = {21},
  number    = {4},
  year      = {1989},
  pages     = {515-556},
  ee        = {db/journals/csur/AdamW89.html},
  bibsource = {DBLP, http://dblp.uni-trier.de}
}

Abstract

This paper considers the problem of providing security to statistical databases against disclosure of confidential information. Security-control methods suggested in the literature are classified into four general approaches: conceptual, query restriction, data perturbation, and output perturbation.

Criteria for evaluating the performance of the various security-control methods are identified. Security-control methods that are based on each of the four approaches are discussed, together with their performance with respect to the identified evaluation criteria. A detailed comparative analysis of the most promising methods for protecting dynamic-online statistical databases is also presented.

To date no single security-control method prevents both exact and partial disclosures. There are, however, a few perturbation-based methods that prevent exact disclosure and enable the database administrator to exercise "statistical disclosure control." Some of these methods, however introduce bias into query responses or suffer from the 0/1 query-set-size problem (i.e., partial disclosure is possible in case of null query set or a query set of size 1).

We recommend directing future research efforts toward developing new methods that prevent exact disclosure and provide statistical-disclosure control, while at the same time do not suffer from the bias problem and the 0/1 query-set-size problem. Furthermore, efforts directed toward developing a bias-correction mechanism and solving the general problem of small query-set-size would help salvage a few of the current perturbation-based methods.

Copyright © 1989 by the ACM, Inc., used by permission. Permission to make digital or hard copies is granted provided that copies are not made or distributed for profit or direct commercial advantage, and that copies show this notice on the first page or initial screen of a display along with the full citation.


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