Abstract: A method for authorizing a financial operation is disclosed, the method comprising: receiving operation data related to a financial operation; obtaining a first biometric mathematical representation of a user; storing an operation mathematical representation representing operation data and the first biometric mathematical representation in an authorization dataset; receiving the authorization dataset; obtaining the operation mathematical representation and the first biometric mathematical representation from the received authorization dataset; receiving a capture of a second image of the user; generating a second biometric mathematical representation of a user; determining a matching score by comparing the first biometric mathematical representation and the second biometric mathematical representation; authenticating an identity of the user; obtaining the operation data from the operation mathematical representation; and authorizing the financial operation if the identity is authenticated and the operation da

Abstract: Methods are provided for generating an electronic signature, for authenticating said electronic signature, for authenticating integrity of a content signed with said electronic signature, and for authenticating an identity of a signatory who signed said electronic signature, along with systems, computer systems and computer programs suitable for performing said methods.

Abstract: Methods and devices for biometric verification are disclosed. During registration or encoding, a first vector representing biometric features of a subject is generated. Machine-readable optical labels based on the first vector are then generated. During validation or decoding, physical characteristics representative of the subject are captured, the physical characteristic containing biometric features of the subject. The biometric features are identified in the captured physical characteristics. A second vector representing the identified biometric features is generated. The machine-readable optical label is read to decode the first vector. The first vector is compared with the second vector to compute a match probability.

Abstract: Methods, systems and computer programs are provided for authenticating an identity of a person, which includes: obtaining, from a capturing device, one or more captures including image and/or audio captures; detecting, based on spoofing-detection criteria, spoofing indicators in the captures and whether said spoofing indicators correspond to spoofing indicia; detecting, based on liveness-detection criteria, biometric-features in the captures and whether said biometric-features correspond to liveness indicia; detecting, based on identity-biometric criteria, biometric attributes in the captures and whether said biometric attributes correspond to a predefined human identity; extracting, based on time-related criteria, a time-reference hidden or codified in the captures and detecting whether said time-reference satisfies predefined time constraints; and authenticating the identity of the person depending on whether spoofing indicia have been detected, whether liveness indicia have been detected, whether biometric

Abstract: Methods and devices for performing user authorisations using biometric features are disclosed. User identifiers and biometric features of the users are registered in an identification server. Users are identified by their user identifiers, the users being in communication range with an authorisation module. A shortlist of users is generated based identified user identifiers. Biometric features of the users are captured at the authorisation module. The biometric features presented are compared with biometric features stored in the identification server to generate a match probability. Users are validated if the match probability exceeds a threshold. User authorisation is performed when the users are identified and validated.

Abstract: Methods and devices for biometric verification are disclosed. During registration or encoding, a first vector representing biometric features of a subject is generated. Machine-readable optical labels based on the first vector are then generated. During validation or decoding, physical characteristics representative of the subject are captured, the physical characteristic containing biometric features of the subject. The biometric features are identified in the captured physical characteristics. A second vector representing the identified biometric features is generated. The machine-readable optical label is read to decode the first vector. The first vector is compared with the second vector to compute a match probability.