Anonymization download




















Along with all the privacy concerns around data, it even takes GDPR and other data compliances into consideration. Purchase: You can request a demo to get started and then the sales team is going to guide you for further steps. But in case, you come up with a very specific scenario, then you can use a simple extension, wherein you can enter your own logic.

It is easy to implement across a wide variety of databases and can be repeated as and when required. You can perform numerous operations on the database, which include; masking data with random values, intermixing of data records, statistical noise can be added to randomize data, and many more.

Purchasing: A trial version of the product is available for 7 days. For further details, check out their licensing terms and contact their sales team. What are the Best Practices for Data Lineage? YourTechDiet is the most refined repository of content for professionals, currently serving thousands of B2B partner sites worldwide.

Subscribe to our Blogs and read at your own pace Please leave this field empty. Please leave this field empty. In the list below you can find some open source anonymization tools. We paid special attention to actuality, so that the software is still supported and updated. It supports different privacy models like k-anonymity or its variants l-diversity, t-closeness, b-likeness or Differential Privacy and can be used for up to 50 dimensions e. It also has a comprehensive graphical user interface.

Amnesia is a data anonymsation tool that has its background at the Athena Research Center. It supports k-anonymity and km-anonymity. Amnesia has an hierarchy creator and editor that allows the user to tailor the anonymization to find the right balance between privacy and data utility.

The installer can also be downloaded on the website. If you just want to give it a quick spin, there is also an online-version without the need to install anything. The tool uses a wide range of different statistical anonymization methods such as global recoding grouping of categories , local suppression, randomisation, adding noise, microaggregation, top- and bottom coding. It can also be used to generate synthetic data. Latest commit. Git stats commits. Failed to load latest commit information.

View code. Data::Anonymization Data Anonymization tool helps build anonymized production data dumps, which you can use for performance testing, security testing, debugging and development. Blacklist database. Whitelist source, dest. About Data Anonymization implementation in Kotiln dataanon. Releases No releases published. Packages 0 No packages published. Contributors 4. You signed in with another tab or window. Reload to refresh your session.

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