Biometrics Data Space: Ensuring Trustworthy and Secure Data Exchange for Suspect Identification

Concerns about privacy protection, ethics, and the urgency to adhere to EU regulations for personal data protection are increasing as digital biometric technologies are widely being adopted in order to improve the accuracy of the identification and verification processes. This paper proposes the formation of a Biometrics Data Space, a trusted ecosystem that is based on the Data Spaces technology and offers secure sharing and exchange capabilities of biometric data in potential use cases, such as foreign Law Enforcement Agencies (LEAs) and forensic agencies, with an aim to facilitate the process of reliable identification of the suspects. The suggested identification framework incorporates Privacy Enhancing Technologies (PETs), such as homomorphic encryption, to address data protection concerns. Moreover, Large-Scale Data Indexing is applied to the biometric data to provide a fast and efficient comparison o fag iven facial image with ones stored in owners' local premises and without disclosing any personal information during the search and match process. Furthermore, automated access rights control is implemented by Blockchain Smart Contracts that are integrated into the Biomet-rics Data Space framework. The main objective of the suggested framework is to offer a reliable and automated identification system that ensures trust, data sovereignty, interoperability, and robust data protection.