Unfortunately, data anonymization techniques have largely ignored diversity in its published result. This inadvertently propagates underlying bias in subsequent data analysis. We study the problem of finding a diverse anonymized data instance where diversity is measured via a set of diversity constraints.
Nov 30, 2021 · We study the problem of finding a diverse anonymized data instance where diversity is measured via a set of diversity constraints. We formalize ...
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Jul 17, 2020 · Anonymization is the most common form of PPDP, where quasi-identifiers and/or sensitive values are obfuscated via suppression or generalization ...
Apr 1, 2023 · We study the problem of finding a diverse anonymized data instance where diversity is measured via a set of diversity constraints. We formalize ...
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We formalize diversity constraints, and study their fundamental problems of satisfiability, implication, and validation. We show that determining the existence ...
[PDF] Preserving Diversity in Anonymized Data - OpenProceedings.org
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Mar 26, 2021 · We study the problem of finding a diverse anonymized data instance where diversity is measured via a set of diversity constraints.
Jul 17, 2020 · This diversity is desirable in many applications ranging from Web search to drug and product development. Unfortunately, data anonymization ...
May 16, 2024 · Under GDPR, anonymized data is not considered personal data, so it is not subject to the same regulatory constraints. For example, anonymized ...
Sep 9, 2023 · Anonymized data undergoing K Anonymity and L Diversity is cleaner and more compliant. This enables organizations to drive digital transformation ...
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Publishing data about individuals without revealing sen- sitive information about them is an important problem. In recent years, a new definition of privacy ...