<p>Data masking is a <a href=”https://www.techtarget.com/searchsecurity/Data-security-guide-Everything-you-need-to-know”>security</a> technique that modifies sensitive data in a data set so it can be used safely in a non-production environment. Masking allows software developers, software testers, software application trainers and data analysts to work with an organization’s data without putting confidential information at risk or violating compliance regulations designed to protect personally identifiable information (<a href=”https://www.techtarget.com/searchsecurity/definition/personally-identifiable-information-PII”>PII</a>).</p>
<p>Data masking is most often used to protect <a href=”https://www.techtarget.com/whatis/definition/structured-data”>structured data</a> in software development environments and in situations where data sets that contain confidential information need to be shared between systems or with third-party partners. To be used effectively, masked data should be able to pass validation checks and maintain consistent relationships across tables, but not be able to be <a href=”https://www.techtarget.com/searchsoftwarequality/definition/reverse-engineering”>reverse-engineered</a>.</p>
<p>Data masking uses <a href=”https://www.techtarget.com/searchsecurity/definition/obfuscation”>data obfuscation</a> techniques like scrambling and substitution to change confidential data values, while still preserving <a href=”https://www.techtarget.com/searchapparchitecture/definition/data-type”>data types</a> and <a href=”https://www.techtarget.com/whatis/definition/file-format”>file formats</a>. This allows the masked data to behave just like the original data in non-production environments but prevents it from being used for identity theft, fraud or other malicious reasons.</p>
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<p>Masked data is considered to be a pseudonymized <a href=”https://www.techtarget.com/searchdatamanagement/definition/data-de-identification”>data de-identification</a>
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