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Inference Control in Statistical Databases, From Theory to Practice

Inference Control in Statistical Databases, From Theory to Practice,Josep Domingo-Ferrer

Inference Control in Statistical Databases, From Theory to Practice   (Citations: 18)
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    • ...Information leaks from the outcome of the computation can be a concern and is controlled under our framework using existing techniques for query auditing and inference control [42, 59, 54, 55, 32, 25]...
    • ...Information leaks from the outcome should also be controlled: in Section 3.4, we describe a simple technique that evaluates information leaks through constraint solving; in general, we can treat individual nucleotides as attributes, with SNPs being marked as sensitive, and apply existing query auditing [42, 59, 54, 55, 32] and inference control techniques [25] to check the query...
    • ...Instead, it is just a component of our framework and can be replaced with other existing technologies for query auditing [59, 42] and inference control [42, 59, 54, 55, 32, 25]...

    Rui Wanget al. Privacy-preserving genomic computation through program specialization

    • ...The protection of privacy in statistical database (SDB) has been a problem of growing concern in recent years [4]...

    Gerardo Canforaet al. A Bayesian Approach for on-Line Max Auditing

    • ...The protection of privacy in statistical database (SDB) has been a problem of growing concern in recent years [5]...

    Gerardo Canforaet al. A Bayesian approach for on-line max and min auditing

    • ...In fact, it should be noted that our research is fully contextualized in the Statistical Disclosure Control (SDC) scientific field proposed by Domingo-Ferrer in [13], which is a widely-recognized authoritative research contribution...
    • ...In this context, two meaningful measures for evaluating the accuracy and privacy preservation capabilities of an arbitrary method/technique have been introduced [13]...
    • ...As accuracy metrics for answers to queries, we make use of the relative query error between exact and approximate answers, which is a well-recognized-in-literature measure of quality for approximate query answering techniques in OLAP (e.g., [6,13])...

    Alfredo Cuzzocreaet al. A Robust Sampling-Based Framework for Privacy Preserving OLAP

    • ...The kanonymity model [12, 14], � -diversity model [8] and similar works like [11], on statistical databases [5], and deductive databases [2] address the problem of releasing personal information so that the subjects of the data cannot be identified uniquely...

    Indrajit Rayet al. Facilitating Privacy Related Decisions in Different Privacy Contexts o...

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