Enter the realm of crypto-biometrics
To strike a balance between safeguarding data and facilitating necessary authentication (such as user verification or account association), crypto-biometrics integrates a spectrum of technologies. Situated at the confluence of mathematics, information security, cybersecurity, sybil resistance, biometric technology, liveness detection, zero-knowledge proof (ZKP) technologies, encryption, and blockchain technology, it orchestrates a multidisciplinary approach to security.
How Biometric ID’s are Utilized in Bitssurance
Bitssurance harnesses biometric identification of users for two primary objectives:
1. To ascertain the registration status of a user.
2. Grant access to the array of services associated with the user upon confirmation of registration.
When a user initiates their involvement in the Bitssurance network to become a human node (validator node), they undergo registration of their biometric data. For the main-net launch, users will likely be required to register multiple (potentially three) biometric modalities, encompassing features like face, iris, retina, ear, fingerprint, palm-print, finger/hand vein recognition, etc. This registration process involves a live video-based 3D face scan and liveness detection, ensuring the authenticity of the user as a living individual. Upon validation of being an unregistered living person (thus not a deep fake, photo, 2D/3D mask, mannequin, or deceased individual), the 3D face mapping vector undergoes conversion into numerical values and encryption, enabling computational operations on encrypted data without decryption.
2. Grant access to the array of services associated with the user upon confirmation of registration.
When a user initiates their involvement in the Bitssurance network to become a human node (validator node), they undergo registration of their biometric data. For the main-net launch, users will likely be required to register multiple (potentially three) biometric modalities, encompassing features like face, iris, retina, ear, fingerprint, palm-print, finger/hand vein recognition, etc. This registration process involves a live video-based 3D face scan and liveness detection, ensuring the authenticity of the user as a living individual. Upon validation of being an unregistered living person (thus not a deep fake, photo, 2D/3D mask, mannequin, or deceased individual), the 3D face mapping vector undergoes conversion into numerical values and encryption, enabling computational operations on encrypted data without decryption.
Following this process, public and private keys are generated, facilitating the creation of the user's node
Upon node launch, the encrypted user identity is disseminated to all network nodes, which store the received encrypted feature vectors for subsequent matching operations (ranging from one to many). It’s noteworthy that the video and actual biometric data utilized to create the encrypted 3D feature vector never leaves the user’s node.
For registered users, accessing services tied to their account post-login entails proving identity and verifying their vitality. The encrypted space hosts the one-to-many search and matching operation during login. Leveraging Zero-Knowledge Proof (ZKP) technology ensures that only the status of user registration is sought and disclosed.
In essence, the system is architected to provide the utmost security for users while facilitating usability in search and matching operations. It mitigates the risk of centralization, fosters network growth based on hardware with defined specifications, or across various cloud-based platforms.
