Security of Statistical Databases with an Output Perturbation Technique.
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| Title: | Security of Statistical Databases with an Output Perturbation Technique. |
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| Authors: | Adam, Nabil R.1, Jones, Douglas H.2 |
| Source: | Journal of Management Information Systems. Summer89, Vol. 6 Issue 1, p101-110. 10p. |
| Subjects: | Computers in statistics, Database security, Perturbation theory, Database management, Computer security, Regression analysis, Statistical services |
| Abstract: | A statistical database aims at providing users with statistics about the population while not compromising the confidentiality of the individuals whose data are included in the database. Threats to the database security range from issuing cleverly designed sequences of queries to using such sophisticated methods as regression analysis. In order to overcome this security problem, several solution methods have been suggested in the literature. These methods can be classified under four general approaches: conceptual modeling; query restriction; data perturbation; and output perturbation. These methods, however, can be easily compromised, or require excessive CPU and memory, or result in biased response to users. The purpose of this paper is to propose a new type of output perturbation method that may be very difficult to compromise and provides unbiased response. The method is based on recoiling of the data, the jackknifing concept, and an extension of the random sample queries method suggested by Denning [5]. A comparison of the proposed method and the modified random sample queries method (which is considered a viable alternative for security of statistical databases) is presented. [ABSTRACT FROM AUTHOR] |
| Copyright of Journal of Management Information Systems is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Database: | Engineering Source |
| FullText | Links: – Type: pdflink Text: Availability: 0 |
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| Header | DbId: egs DbLabel: Engineering Source An: 5757772 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: Security of Statistical Databases with an Output Perturbation Technique. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Adam%2C+Nabil+R%2E%22">Adam, Nabil R.</searchLink><relatesTo>1</relatesTo><br /><searchLink fieldCode="AR" term="%22Jones%2C+Douglas+H%2E%22">Jones, Douglas H.</searchLink><relatesTo>2</relatesTo> – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22Journal+of+Management+Information+Systems%22">Journal of Management Information Systems</searchLink>. Summer89, Vol. 6 Issue 1, p101-110. 10p. – Name: Subject Label: Subjects Group: Su Data: <searchLink fieldCode="DE" term="%22Computers+in+statistics%22">Computers in statistics</searchLink><br /><searchLink fieldCode="DE" term="%22Database+security%22">Database security</searchLink><br /><searchLink fieldCode="DE" term="%22Perturbation+theory%22">Perturbation theory</searchLink><br /><searchLink fieldCode="DE" term="%22Database+management%22">Database management</searchLink><br /><searchLink fieldCode="DE" term="%22Computer+security%22">Computer security</searchLink><br /><searchLink fieldCode="DE" term="%22Regression+analysis%22">Regression analysis</searchLink><br /><searchLink fieldCode="DE" term="%22Statistical+services%22">Statistical services</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: A statistical database aims at providing users with statistics about the population while not compromising the confidentiality of the individuals whose data are included in the database. Threats to the database security range from issuing cleverly designed sequences of queries to using such sophisticated methods as regression analysis. In order to overcome this security problem, several solution methods have been suggested in the literature. These methods can be classified under four general approaches: conceptual modeling; query restriction; data perturbation; and output perturbation. These methods, however, can be easily compromised, or require excessive CPU and memory, or result in biased response to users. The purpose of this paper is to propose a new type of output perturbation method that may be very difficult to compromise and provides unbiased response. The method is based on recoiling of the data, the jackknifing concept, and an extension of the random sample queries method suggested by Denning [5]. A comparison of the proposed method and the modified random sample queries method (which is considered a viable alternative for security of statistical databases) is presented. [ABSTRACT FROM AUTHOR] – Name: AbstractSuppliedCopyright Label: Group: Ab Data: <i>Copyright of Journal of Management Information Systems is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.) |
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| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.1080/07421222.1989.11517851 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 10 StartPage: 101 Subjects: – SubjectFull: Computers in statistics Type: general – SubjectFull: Database security Type: general – SubjectFull: Perturbation theory Type: general – SubjectFull: Database management Type: general – SubjectFull: Computer security Type: general – SubjectFull: Regression analysis Type: general – SubjectFull: Statistical services Type: general Titles: – TitleFull: Security of Statistical Databases with an Output Perturbation Technique. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Adam, Nabil R. – PersonEntity: Name: NameFull: Jones, Douglas H. IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 06 Text: Summer89 Type: published Y: 1989 Identifiers: – Type: issn-print Value: 07421222 Numbering: – Type: volume Value: 6 – Type: issue Value: 1 Titles: – TitleFull: Journal of Management Information Systems Type: main |
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