Anonybit smashes the honeypot with first 1:N identification via decentralized cloud

Decentralized biometrics specialist Anonybit has achieved an industry first by adding 1:N (one to many) biometric identification capabilities to its decentralized biometrics cloud service. The product demonstrates that even large-scale deployments such as government ID applications can be securely decentralized.

This privacy-by-design addition means that individuals’ biometrics are broken into anonymized bits which are distributed over a wide network, encrypted and stored ready for future matching. When a verification is required, these scattered biometric fragments do not need to be reassembled, which eliminates the risk of a data breach according to the New York-based firm.

The system allows decentralized deduplication at the point of enrollment and lookup functionalities, meaning the firm can supply privacy-preserving services across many use cases that require 1:N rather than just simpler 1:1 matching.

The service will be available as an add-on in Anonybit’s turnkey decentralized authentication product and be available to other biometric solution providers, allowing them to use a decentralized cloud that is compliant with GDPR and California’s CPRA.

Facial, fingerprint, iris and voice biometrics modalities and algorithms are all supported for third-party biometrics providers.

The product also handles liveness detection, decentralized storage and 1:1 matching.

“Our goal is to cut off the oxygen that feeds identity thieves by giving them nothing to find and nothing to steal, even if they do manage to break into a network,” comments Frances Zelazny, Anonybit co-founder and chief executive officer.

“By eliminating central honeypots while still enabling strong authentication of biometrics, we are ushering in a new era for privacy and security, enabled by our innovative decentralized biometrics infrastructure. The one-to-many capability is a cornerstone to creating this future, allowing governments, enterprises, and other entities to ensure a privacy-first system of record for individuals based on their biometrics. This creates an anchor of trust that supports all other types of deployments, like verifiable credentials, online account access, time and attendance systems, payments and others.”

Zelazny explained Anonybit’s ambitions, and the potential advantages of its storage architecture for biometric identification and deduplication processes, in an interview with Biometric Update last year.

Anonybit recently partnered with face biometrics developers Aware to build secure biometric templates for government use, and FacePhi to build decentralized storage into a smart city project. This followed a $3.5 million funding round to develop storage of sensitive data so that biometrics providers do not have to.

Article Topics

Anonybit  |  anonymization  |  biometric data  |  biometric identification  |  biometric matching  |  biometrics  |  cloud services  |  data protection  |  data storage  |  decentralized biometrics  |  privacy by design