Abstract: The disclosed exemplary embodiments include computer-implemented devices, apparatuses, and processes that, among other things, perform dynamic biometric authentication based on distributed ledger data. For example, a device may compute a first hash value based on first biometric data captured by a sensor unit, and may transmit a request to, and receive a response from, a computing system across a communications network via the communications unit. The request may cause the computing system to execute instructions maintained within the distributed ledger data, and to extract second biometric data maintained within an element of the distributed ledger data. The second biometric data may include a second hash, which the computing system may incorporate into the response. The device may authenticate an identity associated with the device when the first hash value corresponds to the second hash value incorporated within the response.

Abstract: The disclosed exemplary embodiments include computer-implemented systems, apparatuses, and processes that, among other things, generate and provision digital tokens based on dynamically obtained contextual data. For example, an apparatus may receive first information that characterizes an exchange of data initiated by a first application program executed by the apparatus, and may generate and transmit a signal to a computing system through a programmatic interface associated with a second application program executed by the apparatus. In some instances, the first signal may include the first information and data that instructs the computing system to obtain a digital token representative of a data type available for use in the data exchange. The apparatus may also receive a second signal that includes the digital token and based on the digital token, perform operations that present second information characterizing the available data type on an interface.

Abstract: The disclosed exemplary embodiments include computer-implemented systems, apparatuses, and processes that, among other things, generate and provision digital tokens based on dynamically obtained contextual data. For example, an apparatus may receive first information that characterizes an exchange of data initiated by a first application program executed by the apparatus, and may generate and transmit a signal to a computing system through a programmatic interface associated with a second application program executed by the apparatus. In some instances, the first signal may include the first information and data that instructs the computing system to obtain a digital token representative of a data type available for use in the data exchange. The apparatus may also receive a second signal that includes the digital token and based on the digital token, perform operations that present second information characterizing the available data type on an interface.

Abstract: The disclosed exemplary embodiments include computer-implemented devices, apparatuses, and processes that, among other things, perform dynamic biometric authentication based on distributed ledger data. For example, a device may compute a first hash value based on first biometric data captured by a sensor unit, and may transmit a request to, and receive a response from, a computing system across a communications network via the communications unit. The request may cause the computing system to execute instructions maintained within the distributed ledger data, and to extract second biometric data maintained within an element of the distributed ledger data. The second biometric data may include a second hash, which the computing system may incorporate into the response. The device may authenticate an identity associated with the device when the first hash value corresponds to the second hash value incorporated within the response.

Abstract: The disclosed exemplary embodiments include computer-implemented devices, apparatuses, and processes that, among other things, perform dynamic biometric authentication based on distributed ledger data. For example, a device may compute a first hash value based on first biometric data captured by a sensor unit, and may transmit a request to, and receive a response from, a computing system across a communications network via the communications unit. The request may cause the computing system to execute instructions maintained within the distributed ledger data, and to extract second biometric data maintained within an element of the distributed ledger data. The second biometric data may include a second hash, which the computing system may incorporate into the response. The device may authenticate an identity associated with the device when the first hash value corresponds to the second hash value incorporated within the response.

Abstract: The invention is concerned with a method for automatic online detection and classification of anomalous objects in a data stream, especially comprising datasets and/or signals, wherein a) the detection of at least one incoming data stream containing normal and anomalous objects, b) automatic construction of a geometric representation of normality the incoming objects of the data stream at a time t1 subject to at least one predefined optimality condition, especially the construction of a hypersurface enclosing a finite number of normal objects, c) online adaptation of the geometric representation of normality in respect to received at least one received object at a time t2, which is greater than t1, the adaptation being subject to at least one predefined optimality condition, d) online determination of a normality classification for received objects at t2 in respect to the geometric representation of normality, e) automatic classification of normal objects and anomalous objects based on the generated normality