How Google anonymizes data

Anonymization is a data processing technique that removes or modifies personally identifiable information; it results in anonymized data that cannot be associated with any one individual. It’s also a critical component of Google’s commitment to privacy.

By analyzing anonymized data, we are able to build safe and valuable products and features, like autocompletion of an entered search query, and better detect security threats, like phishing and malware sites, all while protecting user identities. We can also safely share anonymized data externally, making it useful for others without putting the privacy of our users at risk.

Two of the techniques we use to protect your data

Generalizing the data

There are certain data elements that are more easily connected to certain individuals. In order to protect those individuals, we use generalization to remove a portion of the data or replace some part of it with a common value. For example, we may use generalization to replace segments of all area codes or phone numbers with the same sequence of numbers.

Generalization allows us to achieve k-anonymity, an industry-standard term used to describe a technique for hiding the identity of individuals in a group of similar pers