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Secure databases: protection against user influence

Editor: David K. Hsiao Authors:

David Dobkin,

Anita K. Jones,

Richard J. LiptonAuthors Info & Claims

ACM Transactions on Database Systems (TODS), Volume 4, Issue 1

Pages 97 - 106

https://doi.org/10.1145/320064.320068

Published: 01 March 1979 Publication History

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Abstract

Users may be able to compromise databases by asking a series of questions and then inferring new information from the answers. The complexity of protecting a database against this technique is discussed here.

References

[1]

CODD, E.F. A relational model of data for large and shared data banks. Comm ACM 13, 6 (June 1970}, 377-387.

Digital Library

Google Scholar

[2]

DEMILLO, R., DOBKIN, D., ANt) LIPTON, R. Even data bases that lie can be compromised. IEEE Trans. Software Eng. SE-4, 1 (1978), 73-75.

Digital Library

Google Scholar

[3]

DENNING, D.E. A lattice model of secure information flow. Comm. ACM 19, 5 (May 1976), 236-243.

Digital Library

Google Scholar

[4]

FENTON, J.S. Memoryless subsystems. Comptr. J. 17, 2 (1974), 143-147.

Crossref

Google Scholar

[5]

GaAHAM, G.S., AND DENNING, P.J. Protection--principles and practice. Proc. AFIPS I972 SJCC, Vol. 40, AFIPS Press, Montvale, N.J., pp. 417-429.

Digital Library

Google Scholar

[6]

HAQ, M. Insuring individuals' privacy from statistical data base users. Proc. AFIPS 1975 NCC, Vol. 43, AFIPS Press, Montvale, N.J., pp. 941-946.

Google Scholar

[7]

HOFFMAN, L.J., AND MILLER, W.F. Getting a personal dossier from a statistical data bank. Datamation 16, 5 (May I970}, 74-75.

Google Scholar

[8]

JONES, A.K., AND LIPTON, R.J. The enforcement of security policies for computation. Proc. 5th Syrup. Oper. Syst. Principles. Oper. SysL Rev. (ACM) 9, 5 (1975), 197-206.

Digital Library

Google Scholar

[9]

JONES, A.K., AND WULF, W.A. Towards the design of secure systems. Software--Practices and Experience 5, 4 (Oct. 1975), 321-336.

Google Scholar

[10]

LAMPSON, B.W. Protection. Proc. 5th Princeton Symp. Inform. Sci. and Syst., 1971, pp. 437-443.

Google Scholar

[11]

ORGANICK, E.I. The MULTICS System: An Examination of Its Structure. M.I.T. Press, Cambridge, Mass., 1972.

Digital Library

Google Scholar

[12]

WULF, W.A., ET AL. HYDRA: The kernel of a multiprocessor system. Comm. ACM 17, 6 (June 1974), 337-345.

Digital Library

Google Scholar

Cited By

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Kondor DHashemian Bde Montjoye YRatti C(2020)Towards Matching User Mobility Traces in Large-Scale DatasetsIEEE Transactions on Big Data10.1109/TBDATA.2018.28716936:4(714-726)Online publication date: 1-Dec-2020
https://doi.org/10.1109/TBDATA.2018.2871693
O'Hearn P(2019)Incorrectness logicProceedings of the ACM on Programming Languages10.1145/33710784:POPL(1-32)Online publication date: 20-Dec-2019
https://dl.acm.org/doi/10.1145/3371078
Luo YGhose SCai YHaratsch EMutlu O(2018)Improving 3D NAND Flash Memory Lifetime by Tolerating Early Retention Loss and Process VariationACM SIGMETRICS Performance Evaluation Review10.1145/3292040.321965946:1(106-106)Online publication date: 12-Jun-2018
https://dl.acm.org/doi/10.1145/3292040.3219659
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Index Terms

Secure databases: protection against user influence
1. Security and privacy
  1. Database and storage security
2. Theory of computation
  1. Theory and algorithms for application domains
    1. Database theory
      1. Theory of database privacy and security

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Published In

cover image ACM Transactions on Database Systems

ACM Transactions on Database Systems Volume 4, Issue 1

March 1979

131 pages

ISSN:0362-5915

EISSN:1557-4644

DOI:10.1145/320064

Editor:
David K. Hsiao
Ohio State Univ., Columbus

Issue’s Table of Contents

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 01 March 1979

Published in TODS Volume 4, Issue 1

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Kondor DHashemian Bde Montjoye YRatti C(2020)Towards Matching User Mobility Traces in Large-Scale DatasetsIEEE Transactions on Big Data10.1109/TBDATA.2018.28716936:4(714-726)Online publication date: 1-Dec-2020
https://doi.org/10.1109/TBDATA.2018.2871693
O'Hearn P(2019)Incorrectness logicProceedings of the ACM on Programming Languages10.1145/33710784:POPL(1-32)Online publication date: 20-Dec-2019
https://dl.acm.org/doi/10.1145/3371078
Luo YGhose SCai YHaratsch EMutlu O(2018)Improving 3D NAND Flash Memory Lifetime by Tolerating Early Retention Loss and Process VariationACM SIGMETRICS Performance Evaluation Review10.1145/3292040.321965946:1(106-106)Online publication date: 12-Jun-2018
https://dl.acm.org/doi/10.1145/3292040.3219659
Chen YSu LXu J(2018)Distributed Statistical Machine Learning in Adversarial SettingsACM SIGMETRICS Performance Evaluation Review10.1145/3292040.321965546:1(96-96)Online publication date: 12-Jun-2018
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Nitu VKocharyan AYaya HTchana AHagimont DAstsatryan H(2018)Working Set Size Estimation Techniques in Virtualized EnvironmentsACM SIGMETRICS Performance Evaluation Review10.1145/3292040.321964246:1(62-63)Online publication date: 12-Jun-2018
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Kleinberg J(2018)Inherent Trade-Offs in Algorithmic FairnessACM SIGMETRICS Performance Evaluation Review10.1145/3292040.321963446:1(40-40)Online publication date: 12-Jun-2018
https://dl.acm.org/doi/10.1145/3292040.3219634
Hou JLi XJung TWang YZheng D(2018)CASTLE: Enhancing the Utility of Inequality Query Auditing Without Denial ThreatsIEEE Transactions on Information Forensics and Security10.1109/TIFS.2018.279780213:7(1656-1669)Online publication date: Jul-2018
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Aravind KAnand ASarath G(2017)Inference detection in statistical database using frequent pattern2017 International Conference on Communication and Signal Processing (ICCSP)10.1109/ICCSP.2017.8286741(1953-1956)Online publication date: Apr-2017
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Guarnieri MMarinovic SBasin D(2017)Securing Databases from Probabilistic Inference2017 IEEE 30th Computer Security Foundations Symposium (CSF)10.1109/CSF.2017.30(343-359)Online publication date: Aug-2017
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Holohan NLeith DMason O(2016)Differentially private response mechanisms on categorical dataDiscrete Applied Mathematics10.1016/j.dam.2016.04.010211:C(86-98)Online publication date: 1-Oct-2016
https://dl.acm.org/doi/10.1016/j.dam.2016.04.010
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Database Security

Compromising statistical databases responding to queries about means

Mitigation of malicious modifications by insiders in databases

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