How to Create an Infostructure to Protect Data as a Utility

The dark side of data is obvious. Fraud, counterfeiting, fake news, misinformation and impersonation are all booming in the digital sphere. Digital now dominates how we interact with the world. But people are left increasingly vulnerable, lacking the customary cues they previously used to establish trust. All they have to go on is data.

Bad data is at the heart of all fraud. ‘Card-Not-Present’ payments fraud, for example, uses stolen credit card numbers which are replayed against unwitting merchants. More elaborate impersonations use rich personal data, often harvested from social media profiles, to fool Knowledge-Based Authentication and account-opening processes. Multi-million dollar mortgage frauds are also perpetrated this way.

The emergence of deep fakes — high fidelity computergenerated animations that duplicate real persons — has kicked off another security arms race

Entirely synthetic identities can be created by skilful criminals who know the blind spots of financial security systems.

The emergence of deep fakes — high fidelity computer-generated animations that duplicate real persons — has kicked off another security arms race. In 2019, fraudsters even used a synthetic voice generator to imitate an energy company’s executive, and called a finance officer at the company to request a €220,000 cash transfer to the fraudster’s account.

The public and lawmakers alike have faith in an imagined sci-fi precision of biometric security, but these systems are becoming increasingly fragile in the face of deep fake-based‘presentation attacks’.

All these frauds take advantage of our difficulty detecting digital lies. Citizens, businesses and governments too all urgently require assurance of the accuracy of all data, from credit card