Variant Twin Storyboard

When organisations want to use data but cannot because of ethical, legal, risk, or compliance concerns, it results in a non-productive “tug of war.

BigPrivacy is a data transformation system that transforms digital representations of people - or “Digital Twins” - into privacy-respectful “Variant Twins” of personal data by applying Pseudonymisation-enabled privacy enhancing techniques.

These Variant Twins are use-case-specific, risk-based versions of Digital Twins.

In this diagram, the Digital Twin is the source dataset at the top. It contains identifying fields like last name and quasi-identifying fields like age and gender.

In Step 1, The BigPrivacy system ingests source data as designated by the data controller.

In Step 2, the system enforces a Privacy Transformer Configuration that transforms the data into a schema established by the data controller. Step 2 includes application of Pseudonymisation-enabled privacy techniques to transform the output data into static or deterministic pseudonyms as appropriate for the authorised use.

In Step 3, a randomly generated pseudonym is added to each record - known only to the BigPrivacy system - allowing Variant Twins to be later linked to identity for authorised purposes. Prior to outputting data into a Variant Twin, it is assessed for re-identification risk by grouping records into cohorts and suppressing records that are too unique and pose a risk of re-identification.

The Variant Twin is the dataset at the bottom of the diagram. It has resistance to unauthorised re-identification and can have up to 100% of the data utility of source data enabling you to comply with GDPR requirements for lawful secondary processing and repurposing of data.

Anonos BigPrivacy technology resolves the tug-of-war between legal/compliance and data use/innovation by leveraging state-of-the-art Pseudonymisation to create privacy-respectful Variant Twins.