Pseudonymization and anonymization are both techniques used to protect personal data, but they serve different purposes and have distinct characteristics.
Anonymization involves processing data in a way that makes it impossible to trace back to an individual. This means that all identifiers, both direct (like names and Social Security numbers) and indirect (like zip codes or birth dates), are removed or generalized. Once anonymized, the data cannot be re-identified, even with access to other datasets, making it exempt from regulations like the GDPR.
Pseudonymization, on the other hand, replaces identifiable information with pseudonyms or tokens but retains the ability to re-identify individuals if needed. This method allows organizations to use the data for internal purposes while keeping the individuals’ identities protected. Pseudonymized data is still considered personal data under regulations like the GDPR, as it can be re-linked to the individual with additional information, such as encryption keys or other datasets.
In practical terms, pseudonymization is often preferred when data needs to remain useful for analysis or business purposes, as it maintains the structure and detail of the dataset. Anonymization is more suitable for situations where the risk of re-identification must be completely eliminated, such as sharing data with third parties
Lets discuss data security and see fundamentally about the difference between anonymization and pseudonymisation. So why is this important in the past few years billions of data records have been stolen and according to statistics only 4% of them were protected in a way that they were useless for attackers so the rest may very well be for sale in the dark web and to help companies to deal with those breaches there are regulations and standards that describe how to protect the data why a few of them are fairly specific when it comes to describing the protection methods most of them are pretty wake and anonymization and pseudonymisation are in the broad discussion since they appeared in GDPR so what is the difference the difference between two the pseudonymisation and anonymization is basically all about the ability to de-identify personal information so let's talk about an anonymization first when
Anonymization
anonymized data is changed in a way that the individual can no longer be identified you can do that for example by masking or deletion so one benefit of anonymization is that the Risks of Anonymization data is not considered personal identifiable information anymore and you can use it in any way you want a problem of anonymization is that it's a risky thing while it sounds fairly simple in real life you have to make sure that there is no correlation between different data bases that allows the identification of an individual and that you've changed the data in a way that it's really anonymizing that personal identifiable information and it's irreversible which means you can't get back to the original data set which might not be the right solution when it comes to a processing of data analytics for example on the other side we have pseudonymisation
Anonymisation
when pseudonymous data is processed in a way that it cannot be attributed to a specific person without the use of additional information so data is only then considered really pseudonymous when you keep this information this secret separate from the data as pseudonymisation is reversible it is still considered personal identifiable information and you have to have consent to use that data but the good thing is according to GDPR if the data is protected with trump protection methods you don't have to disclose a breach if the data gets stone so there are many ways to implement both techniques but for pseudonymization tokenization is a fairly good approach because it still keeps the usability of the data and it allows you to monetize the data