{"id":4917,"date":"2021-08-23T15:56:02","date_gmt":"2021-08-23T13:56:02","guid":{"rendered":"https:\/\/www.arcadsoftware.com\/dot\/?page_id=4917"},"modified":"2025-10-16T15:51:23","modified_gmt":"2025-10-16T13:51:23","slug":"data-masking","status":"publish","type":"page","link":"https:\/\/www.arcadsoftware.com\/dot\/data-masking\/","title":{"rendered":"Masking of personal and identifying data"},"content":{"rendered":"

\"Data<\/span><\/div>

Data Masking<\/h1><\/div>

Mask your personal data while ensuring it looks and acts like real data<\/p>\n<\/div>

Watch a demo<\/span><\/a><\/div><\/div><\/div>
\"DOT<\/span><\/div><\/div><\/div><\/div><\/div>
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Data masking and anonymization<\/h2><\/div><\/div><\/div>

Data masking<\/strong> is a technology which aims to prevent the manipulation of personal data by giving users fictitious data (but realistic) instead of real personal data.<\/p>\n<\/div><\/div><\/div>

The anonymization<\/strong> of personal data consists in modifying the content or structure<\/strong> of this data in order to make it impossible to \u201cre-identify\u201d<\/strong> users (physical or legal) or entities concerned.<\/p>\n<\/div><\/div><\/div><\/div><\/div>

Personal data exposed to staff<\/h3><\/div>

With the constitution of test data sets intended to populate different environments (such as test, Quality Assurance (QA), qualification, training, dedicated to young recruits, etc…), there is a growing risk of personal and confidential data originating from production becoming visible to unauthorized staff such as testers, QA staff and developers. These users are not authorized to visualize this personal production data (name of persons, addresses, mobile numbers, bank account numbers, social security details) and can introduce a potential data leak. Since the security level of development servers are not as high as production servers, a desensitization of personal and confidential data is needed.<\/p>\n<\/div><\/div><\/div>

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“70% of security incidents come from internal sources” -Gartner<\/p>\n<\/blockquote>\n<\/div><\/div><\/div><\/div><\/div>

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Learn how to protect your business from data leakage<\/p>\n<\/div><\/div><\/div><\/div><\/div>

To be effective, anonymization must preserve the usability of data:<\/h4><\/div>
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    Maintain its readability (preservation of the data format)<\/div><\/li>
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    Maintain data format and type (an address must remain an address for example)<\/p>\n<\/div><\/li>

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    Retains values from one transformation to another<\/p>\n<\/div><\/li>

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    Ensures cross-platform consistency (the same anonymization rule used in different databases)<\/div><\/li><\/ul><\/div><\/div><\/div><\/div>

    Take a look at our infographic and find out how Data Masking<\/a> can anonymize production data while maintaining its usability. To go even further, check out our article about the 5 most common questions about data anonymization<\/a>.<\/p>\n<\/div>