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Probabilistic Information Loss Measures in Confidentiality Protection of Continuous Microdata
2005
Data mining and knowledge discovery
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We propose in this paper to use probabilities to define bounded information loss measures for continuous microdata. ...
Inference control for protecting the privacy of microdata (individual data) should try to optimize the tradeoff between data utility (low information loss) and protection against disclosure (low disclosure ...
Acknowledgments Thanks go to Jordi Castellà for his help in preparing the web form http://vneumann.etse.urv.es/SDC/measures. ...
doi:10.1007/s10618-005-0011-9
fatcat:ylah5mgxyndwjevw6r2s3a27zu
A Survey of Inference Control Methods for Privacy-Preserving Data Mining
[chapter]
2008
Privacy-Preserving Data Mining
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In this chapter, we survey the current state of the art in SDC methods for protecting individual data (microdata). ...
We discuss several information loss and disclosure risk measures and analyze several ways of combining them to assess the performance of the various methods. ...
is the information loss measure defined above. ...
doi:10.1007/978-0-387-70992-5_3
dblp:series/ads/Domingo-Ferrer08
fatcat:56egem63mnenrghswpppdtad5e
Microdata Protection
[chapter]
2007
Advances in Information Security
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Information loss is the amount of information that exists in the original microdata and because of the protection technique does not occur in protected microdata. ...
The information loss measure uses the conditional probability (the probability of a value in the original microdata, once the value in the protected microdata is given). ...
doi:10.1007/978-0-387-27696-0_9
fatcat:4joa23cca5efvkcsmya7xvk7bi
Statistical Disclosure Control Methods for Microdata from the Labour Force Survey
2020
Acta Universitatis Lodziensis. Folia Oeconomica
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In the first step, the author assessed to what extent the confidentiality of information was protected in the original dataset. ...
In the second step, after applying selected methods implemented in the sdcMicro package in the R programme, the impact of those methods on the disclosure risk, the loss of information and the quality of ...
The measurement of microdata utility The R programme report does not contain a universal measure of information loss in the case of perturbing categorical variables, although two measures are available ...
doi:10.18778/0208-6018.348.01
fatcat:e7lo55b2kzbu5lg25d67ra2jvu
Privacy and confidentiality
[chapter]
2003
Plant Engineering Series
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Information loss measure, introduced in this paper, extends the existing measure proposed by Domingo-Ferrer, and captures the loss of information at record level as well as from the statistical integrity ...
The maximal disclosure risk measure considers the risk associated with probabilistic record linkage for records that are not unique in the masked microdata. ...
The information loss measure is an extension of the work presented in [7] regarding continuous microdata. The measures presented in this paper are validated in our experiments. ...
doi:10.1201/9780203508763.ax3
fatcat:f2b3tmgvnjb3tm3avytg26vrvi
Privacy and confidentiality management for the microaggregation disclosure control method
2003
Proceeding of the ACM workshop on Privacy in the electronic society - WPES '03
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Information loss measure, introduced in this paper, extends the existing measure proposed by Domingo-Ferrer, and captures the loss of information at record level as well as from the statistical integrity ...
The maximal disclosure risk measure considers the risk associated with probabilistic record linkage for records that are not unique in the masked microdata. ...
The information loss measure is an extension of the work presented in [7] regarding continuous microdata. The measures presented in this paper are validated in our experiments. ...
doi:10.1145/1005140.1005144
dblp:conf/wpes/TrutaFC03
fatcat:kc62spms5nefpga4lkqz3kcr74
Synthetic Business Microdata
2020
Journal of Privacy and Confidentiality
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Enhancing microdata access is one of the strategic priorities for the Australian Bureau of Statistics (ABS) in its transformation program. ...
This means the existing microdata protection techniques such as information reduction or perturbation may not be as effective as for household microdata. ...
However, it is often difficult to quantify the amount of information loss or level of protection achieved using confidentialised input approaches. ...
doi:10.29012/jpc.733
fatcat:yhgyou47ivbprpzlu7frld5xly
Statistical Disclosure Limitation: New Directions and Challenges
2018
Journal of Privacy and Confidentiality
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There is now more recognition of the need for perturbative methods to protect the confidentiality of data subjects. ...
In particular, inferential disclosure is the main disclosure risk of concern and encompasses the traditional types of disclosure risks based on identity and attribute disclosures. ...
One of the first approaches to quantify disclosure risk in survey microdata was by record linkage (distance-based or probabilistic) where the confidentialized data was matched back to the original data ...
doi:10.29012/jpc.684
fatcat:pfj46hofrzbz7pnnieruinpz64
Survey on Privacy-Preserving Techniques for Data Publishing
[article]
2022
arXiv
pre-print
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We present existing privacy-preserving techniques used in microdata de-identification, privacy measures suitable for several disclosure types and, information loss and predictive performance measures. ...
However, de-identified data usually results in loss of information, with a possible impact on data analysis precision and model predictive performance. ...
In general, information loss is measured during the generalisation process. ...
arXiv:2201.08120v1
fatcat:d7jy6jnuwbftpnahf4ywklztje
Post-Masking Optimization of the Tradeoff between Information Loss and Disclosure Risk in Masked Microdata Sets
[chapter]
2002
Lecture Notes in Computer Science
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Previous work by these authors has been directed to measuring the performance of microdata masking methods in terms of information loss and disclosure risk. ...
The technique proposed can also be used for synthetic microdata generation and can be extended to preservation of all moments up to m-th order, for any m. ...
This is a substantial step forward in optimizing the tradeoff between information loss and disclosure risk in microdata protection. ...
doi:10.1007/3-540-47804-3_13
fatcat:5e5qolzmhzhercyv2gaufdcsia
Ordinal, Continuous and Heterogeneous k-Anonymity Through Microaggregation
2005
Data mining and knowledge discovery
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k-Anonymity is a useful concept to solve the tension between data utility and respondent privacy in individual data (microdata) protection. ...
However, the generalization and suppression approach proposed in the literature to achieve k-anonymity is not equally suited for all types of attributes: (i) generalization/suppression is one of the few ...
Acknowledgments Francesc Sebé's help in obtaining the results reported for continuous data is gratefully acknowledged. Comments by William Winkler were also particularly useful to improve this paper. ...
doi:10.1007/s10618-005-0007-5
fatcat:q3rq3iqkhra7thnxk7iiep5424
Providing Data With High Utility And No Disclosure Risk For The Public and Researchers: An Evaluation By Advanced Statistical Disclosure Risk Methods
2014
Austrian Journal of Statistics
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It is shown that the application of few selected anonymisation methods leads to well-protected anonymised data with high data utility and low information loss. ...
The research on SDC methods becomes more and more important in the last years because of an increase of the awareness on data privacy and because of the fact that more and more data are provided to the ...
Measuring disclosure risk Measuring risk in an microdata set is of course of great concern when having to decide on whether a microdata set is safe to be released. ...
doi:10.17713/ajs.v43i4.43
fatcat:t64apiicerby5j2pcbq2sk6auu
Releasing Microdata: Disclosure Risk Estimation, Data Masking and Assessing Utility
2010
Journal of Privacy and Confidentiality
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Statistical Agencies need to make informed decisions when releasing sample microdata from social surveys with respect to the level of protection required in the data and the mode of access. ...
These decisions should be based on objective quantitative measures of disclosure risk and data utility. ...
Shlomo, 2007 and Shlomo and Young, 2006 describe the use of such measures for assessing information loss in perturbed statistical data. ...
doi:10.29012/jpc.v2i1.584
fatcat:iqhxhqsvqfbrpajlon743nys3y
Privacy Protection from Sampling and Perturbation in Survey Microdata
2012
Journal of Privacy and Confidentiality
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and confidential information may be learnt. ...
We discuss these definitions and conditions in the context of survey microdata. We then extend this discussion to the case of perturbation. ...
an individual and confidential information on a sensitive variable may be learnt. ...
doi:10.29012/jpc.v4i1.615
fatcat:7we36e27c5ahrnlkhd2zr26i6e
Statistical Disclosure Risk: Separating Potential and Harm
2012
International Statistical Review
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Statistical agencies are keen to devise ways to provide research access to data while protecting confidentiality. ...
We argue in Section 2.2 that, in the context of many official confidentiality statements, it is appropriate that the probability of disclosure refers to true disclosure. ...
Introduction The challenge of devising ways to provide researchers with access to microdata and other statistical outputs while protecting confidentiality continues to be the subject of intense interest ...
doi:10.1111/j.1751-5823.2012.00194.x
fatcat:izgt6gdyurcepld4my4vhglv4q
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