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.

Are you facing any of these 4 problems with data?

You need a solution that removes the impediments to achieving speed to insight, lawfully & ethically

to Insight
Are you unable to get desired business outcomes from your data within critical time frames? 53% of CDOs cannot achieve their desired uses of data. Are you one of them?
Lack of
Do you have trouble getting access to the third-party data that you need to maximise the value of your data assets? Are third-parties and partners you work with worried about liability, or disruption of their operations?
Inability to
Are you unable to process data due to limitations imposed by internal or external parties? Do they have concerns about your ability to control data use, sharing or combining?
Are you unable to defend the lawfulness of your current data processing activities, or data processing you have done in the past?
Traditional privacy technologies focus on protecting data by putting it in “cages,” “containers,” or limiting use to centralised processing only. This limitation is done without considering the context of what the desired data use will be, including decentralised data sharing and combining. These approaches are based on decades-old, limited-use perspectives on data protection that severely minimise the kinds of data uses that remain available after controls have been applied. On the other hand, many other new data-use technologies focus on delivering desired business outcomes without considering that roadblocks may exist, such as those noted in the four problems above.
Anonos technology allows data to be accessed and processed in line with desired business outcomes (including sharing and combining data) with full awareness of, and the ability to remove, potential roadblocks.