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1. amnesia.openaire.euAmnesia Anonymization Tool - Data anonymization made easy

   amnesia.openaire.eu

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   Use Amnesia to transform personal data to anonymous data that can be used for statistical analysis. Data anonymized with Amnesia are *statistically guaranteed* that they cannot be linked to the original data. Guarantees no links to the original data. Offers k-anonymity & km-anonynity.

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     Download the latest version of Amnesia anonymization tool...

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     Contact with Amnesia anonymization tool's support team. ×...

   • Amnesia New How-To Tutorials

     Amnesia is a flexible, user-friendly, free, and open-source...

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     MONITOR Dashboard - customized portals as-a-service to...

2. github.com › topics › k-anonymityk-anonymity · GitHub Topics · GitHub

   github.com › topics › k-anonymity

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   A simple Python package to quickly run privacy metrics for your data. Obtain the K-anonimity, L-diversity and T-closeness to asses how anonymous your transformed data is, and how it's balanced with data usability.

3. en.wikipedia.org › wiki › K-anonymityk-anonymity - Wikipedia

   en.wikipedia.org › wiki › K-anonymity

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   k-anonymity is a property possessed by certain anonymized data. The term k -anonymity was first introduced by Pierangela Samarati and Latanya Sweeney in a paper published in 1998, [1] although the concept dates to a 1986 paper by Tore Dalenius. [2]

4. cloud.google.com › sensitive-data-protection › docsComputing k-anonymity for a dataset - Google Cloud

   cloud.google.com › sensitive-data-protection › docs

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   15 paź 2024 · A dataset is k-anonymous if quasi-identifiers for each person in the dataset are identical to at least k – 1 other people also in the dataset. You can compute the k -anonymity value based on...

5. github.com › arx-deidentifier › arxARX is a comprehensive open source data anonymization tool ... -...

   github.com › arx-deidentifier › arx

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   ARX is a comprehensive open source data anonymization tool aiming to provide scalability and usability. It supports various anonymization techniques, methods for analyzing data quality and re-identification risks and it supports well-known privacy models, such as k-anonymity, l-diversity, t-closeness and differential privacy. - arx-deidentifier/arx

6. arx.deidentifier.org › development › frameworkFramework | ARX - Data Anonymization Tool

   arx.deidentifier.org › development › framework

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   Typical examples include k-anonymity, l-diversity, t-closeness or δ-presence. The basic idea of k-anonymity is to protect a dataset against re-identification by generalizing the attributes which could be used in a linkage attack (quasi identifiers).

7. www.immuta.com › blog › k-anonymity-everything-you-need-to-know-2021-guideEverything You Need to Know About K-Anonymity - Immuta

   www.immuta.com › blog › k-anonymity-everything-you-need-to-know-2021-guide

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   14 kwi 2021 · What is k-Anonymity? How Can k-Anonymity Help Prevent a Privacy Attack? How Is k-Anonymity Implemented? How is l-Diversity Achieved Using k-Anonymization? Data Masking and De-Identification with Immuta