NDLI: Diophantine inferences from statistical aggregates on few-valued attributes

Content Provider	IEEE Xplore Digital Library
Author	Rowe, Neil C.
Copyright Year	1984
Description	Author affiliation: Department of Computer Science, Code 52, Naval Postgraduate School, Monterey, CA 93943 (Rowe, Neil C.)
Abstract	Research on protection of statistical databases from revelation of private or sensitive information [Denning, 1982, ch. 6] has rarely examined situations where domain-dependent structure exists for a data attribute such that only a very few independent variables can characterize it. Such circumstances can lead to Diophantine (that is, integer-solution) equations whose solution can lead to surprising or compromising inferences on quite large data populations. In many cases the Diophantine equations are linear, allowing efficient algorithmic solution. Probabilistic models can also be used to rank solutions by reasonability, further pruning the search space. Unfortunately, it is difficult to protect against this form of data compromise, and all countermeasures have disadvantages.
Starting Page	107
Ending Page	110
File Size	573635
Page Count	4
File Format	PDF
ISBN	9780818605338
DOI	10.1109/ICDE.1984.7271261
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	1984-04-24
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Mathematical model Remuneration Databases Cryptography Presses Aggregates Computer science
Content Type	Text
Resource Type	Article

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Diophantine inferences from statistical aggregates on few-valued attributes