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Data Anonymization

Artificial Intelligence
Adopt

Data Anonymization is a type of information sanitization whose intent is privacy protection.

It is the process of either encrypting or removing personally identifiable information from data sets, so that the people whom the data describe remain anonymous.

This is crucial for protecting the privacy of individuals and organizations of which data are used and shared for business, scientific research, or other purposes. The goal is to make it impossible or at least very difficult to identify individuals from the anonymized data.

Basically, the approach that we utilize is conceptualized as below:

  1. Every sensitive keyword / term will masked using the following pattern <Subject#RandomNum> before being fed into 3rd-party AI Chat model.

  2. The masked patterns will be read and processed by the 3rd-party AI Chat model, then it will return the same pattern of the sensitive keywords / terms.

  3. Accordingly, a de-masking mechanism is used to restore the original representations of those sensitive keywords / terms.