Embodiments of the invention involve using biometric templates to wirelessly authenticate individuals. In one embodiment, a mobile device may generate a first biometric template and a first public value from a first biometric sample of a user and generate a first cryptographic key by passing the first biometric template to a fuzzy extractors generate function. An access device may generate a second biometric template from a second biometric sample of the user, generate a second secret cryptographic key by passing the second biometric template and the first public value to the fuzzy extractors reproduce function, encrypt the second biometric template with the second secret cryptographic key, and broadcast the encrypted template to a plurality of nearby mobile devices including the mobile device. If the mobile device is able to decrypt the encrypted template with the first cryptographic key, the access device can associate the user with the mobile device.

A user authentication system uses an information code such as a two-dimensional information code. The authentication system includes an authentication device, and the user is authenticated by combining the authentication device with a user's mobile terminal. In the mobile terminal, an authentication code in which facial feature points extracted from user's facial images are recorded is stored in the memory. In the authentication device, facial feature points are extracted from images of a human's face captured by an imaging unit, after being determined to be in a facial recognizable state, and the authentication code is displayed on the screen of the mobile terminal. The e facial feature points recorded in the authentication code are read from the captured images of the authentication code. The extracted facial feature points and the read facial feature points are subject to matching with each other in order to authenticate the user.

Each of a plurality of edge computing devices are configured to receive data streams generated by at least one sensor forming part of a respective medical device (e.g., a sensor-equipped surgical tool, etc.) which, in turn, characterizes use of the respective medical device in relation to a particular patient. Each of the edge computing devices can execute at least one machine learning model which generates or from which model attributes are derived. The generated model attributes are anonymized using an anonymization technique such as k-anonymity. The anonymized generated model attributes are homomorphically encrypted and transmitted to a central server. Encrypted model attribute updates to at least one of the machine learning models are later received from the central server which results in the machine learning models executing on one or more of the edge computing devices to be updated based on the received encrypted model attribute updates.

Examples of a system for usage control of a personal data are described. The system may obtain an input image including a first face of a person. Further, the system may compute a usage control matrix based on the input image, at least one usage control function, and a predefined criteria. The pre-defined criteria may be associated with at least one of: a data usage policy, a face matching probability related to matching of the face present in the input image, and a face recognition probability related to a recognition of an identity of the person. Furthermore, by using the input image and the usage control matrix, the system may transform the input image to a usage-controlled image. Furthermore, the system may verify a matching of the face present in the input image with a second face present in the usage-controlled image. Furthermore, the system may recognize an identity of the person in the input image and provide a feedback indicative of a failure to verify the identity of the person from the usage-controlled image.

There is provided a method and corresponding system for handling and/or generating anonymous biometric and/or behavioural data. The method comprises the steps of mapping (S1) biometric data originating from a subject into a biometric key using a one-way locality-sensitive hash function or receiving the biometric key. The method also comprises storing (S2) additional anonymous behavioural data bound to this key into an existing biometric trajectory in a database, wherein the behavioural data describes the user behavior of the subject. The method is performed to anonymize biometric data from a multitude of individuals, or subjects, per key, where each biometric key maps to biometric data of several subjects, and such a set of subjects resulting in the same biometric key is called a hash group, and a biometric trajectory is developed for each hash group.

A computer alters at least one recognizable metric or text in a digitally encoded photographic image by operating an alteration algorithm in response to user input data while preserving an overall aesthetic quality of the image and obscuring an identity of at least one individual or geographic location appearing in the image. An altered digitally-encoded photographic image prepared by the altering of the at least one recognizable metric or text in the image is stored in a computer memory. User feedback and/or automatic analysis may be performed to define parameter values of the alteration algorithm such that the alteration process achieves preservation of aesthetic qualities while obscuring an identity of interest.

A device and method for achieving a high probability of match for identifying individuals in a particular group, is provided. The device and method consists of two stages. The first stage compares a biometric template against personnel in an authorized group with a high probability of match standard. In the second stage, in response to no match being made in the authorization group, a search would be conducted against a second group, such as a watch list, with the same or lower probability of match rate.

A fingerprint sensing system. The fingerprint sensing system includes: at least one sensor; at least one display device; at least one application processor; and at least one secure enclave processor. The application processor(s) receives fingerprint data from the sensor(s) and provides the fingerprint data to the secure enclave processor(s). The secure enclave processor(s) decodes the fingerprint data and provides a signal indicative of at least one matched node. The application processor(s), responsive to receipt of the signal indicative of the matched node(s), presents at least a portion of a synthetic fingerprint image via at least one display device corresponding to the matched node(s).

A fingerprint identification system comprising a smart device, a fingerprint scanner, a processor coupled to a transceiver and to the fingerprint scanner, and a digital storage element coupled to the processor. The digital storage element stores logic that causes the processor to: activate the fingerprint scanner to scan a user's finger, identify a feature and multiple minutia of the user's fingerprint, and generate a digital fingerprint string(s) indicative of a position of each minutia relative to the feature. The processor is then caused to combine the digital fingerprint string(s) with a first cryptographic salt to generate a first hash. The first hash is compared to a first hash signature to determine if the first hash represents an authentic fingerprint. If authentic, the processor combines the digital fingerprint string(s) with a second cryptographic salt to generate a second hash. This second hash is transmitted to one or more servers.

Embodiments of the invention involve using biometric templates to wirelessly authenticate individuals. In one embodiment, a mobile device may generate a first biometric template and a first public value from a first biometric sample of a user and generate a first cryptographic key by passing the first biometric template to a fuzzy extractors generate function. An access device may generate a second biometric template from a second biometric sample of the user, generate a second secret cryptographic key by passing the second biometric template and the first public value to the fuzzy extractors reproduce function, encrypt the second biometric template with the second secret cryptographic key, and broadcast the encrypted template to a plurality of nearby mobile devices including the mobile device. If the mobile device is able to decrypt the encrypted template with the first cryptographic key, the access device can associate the user with the mobile device.