Biometric data are obtained from biometric sensors on a stand-alone computing device, which may contain an ASIC, connected to or incorporated within it. The computing device and ASIC, in combination or individually, capture biometric samples, extract biometric features and match them to one or more locally stored, encrypted templates. The biometric matching may be enhanced by the use of an entered PIN. The biometric templates and other sensitive data at rest are encrypted using hardware elements of the computing device and ASIC, and/or a PIN hash. A stored obfuscated Password is de-obfuscated and may be released to the authentication mechanism in response to successfully decrypted templates and matching biometric samples. A different de-obfuscated password may be released to authenticate the user to a remote or local computer and to encrypt data in transit. This eliminates the need for the user to remember and enter complex passwords on the device.

Biometric recognition method using a standard electronic processing unit including a first computer and a first memory and a secure electronic processing unit including a second computer and a second memory, the method including the steps of executing a first part of the recognition steps by the standard processing unit and a second part of the recognition steps by the secure electronic processing unit. Device for the execution of that method.

The present invention relates to a method of secure classification of an input data by means of a convolutional neural network, CNN, the method comprising the implementation by data processing means (11a, 11b, 11c, 21) of at least one device (1a, 1b, 1c, 2), of steps of:

(a) Determination, by application of said CNN to said input data, of a first classification vector of said input data associating with each of a plurality of potential classes a representative integer score of the probability of said input data belonging to the potential class, the first vector corresponding to one possible vector among a first finite and countable set of possible vectors, each possible vector of the first set associating with each of the plurality of potential classes an integer score such that said scores of the possible vector constitute a composition of a predefined whole total value;

(b) Construction, from the first vector, of a second classification vector of said input data, such that the second vector also belongs to the first space of possible vectors and has a distance with the first vector according to a given distance function equal to a non-zero reference distance; and return of the second vector as result of the secure classification.

A method is described for encrypting data that provides increase resistance to brute Identify data segments force attacks by parallel computing means, such as by a quantum computer. To encrypt the data, it is separated into a plurality of data segments, and each of the data segments is encrypted using a different encryption key. The encrypted data segments are then arranged as an encrypted data file in Assign encryption order a manner that impedes parallel attack of the encrypted data segments. For example, the lengths of the encrypted data segments may be non-uniform and/or the spacing of the encrypted data segments within the encrypted data file may be non-uniform. Each encrypted segment may contain a pointer to the next segment, thus permitting an authorised recipient to sequentially decrypt the data file without prior knowledge of the lengths and/or spacings of the encrypted data segments.

Image data is run through a neural network, and the neural network produces a vector representation of the image data. Random sparse sampling masks are created. The vector representation of the image data is masked with each of the random sparse sampling masks, the masking generating corresponding sparsely sampled vectors. The sparsely sampled vectors are transmitted to nodes of a consensus network, wherein a sparsely sampled vector of the sparsely sampled vectors is transmitted to a node of the consensus network. Votes from the nodes of the consensus network are received. Whether a consensus is achieved in the votes is determined. Responsive to determining that the consensus is achieved, at least one of identification and verification of the image data may be provided.

A system and methodologies for pattern representation and recognition are provided. A method includes acquiring a representation associated with discriminating information associated with a subject, retrieving an association between a stored representation and an identity of the subject, determining a discrimination score as a function of the representation and the stored representation based on a neighbor similarity score and relationship contextualization process parameters, and executing one or more control actions based on the discrimination score.

The present disclosure discloses a method for managing a fingerprint and a system thereof, which relates to the field of information technology. The method includes that an upper computer builds a connection with a fingerprint card; the upper computer receives an operation from a user and determines a type of the operation, the upper computer sends the collecting fingerprint instruction to the fingerprint card and the fingerprint card collects a fingerprint and returns a collecting fingerprint response to the upper computer if the operation is a collecting fingerprint operation; the upper computer sends the managing fingerprint instruction to the fingerprint card , the fingerprint card finishes a managing operation on the fingerprint according to the managing fingerprint instruction and returns the managing fingerprint response to the upper computer if the operation is a managing fingerprint operation; and the method further comprises the server authenticates the user information.

A payment gateway/processor or system for POS/ATM/Vending Machine/any capable of device, which allows and process transactions using biometric data without use of mobile/cards/wallets by authorized biometric data. Financial institution while issuing accounts (by registering customer using biometric) also assigned virtual biometric account/credit cards and system may process a transaction with captured biometric information only to identify virtual account associated against stored biometric information comply with it. A Payment transaction does not require any physical payment card or any sort of current mode of transaction information. A payment gateway system will authorized the merchant payment from customer's account using stored biometric data while issued/registered from issuer financial institution. If it conflict against the stored biometric information, it may decline the transaction. The customer's biometric (all 10 finger-print) and palm (Left and Right) information or behavioral information stored in Bank/Financial Institute server/Cloud server.

A method of image processing within an image acquisition device. In one embodiment an image including one or more face regions is acquired and one or more iris regions are identified within the one or more face regions. The one or more iris regions are analyzed to identify any iris region containing an iris pattern that poses a risk of biometrically identifying a subject within the image. Responsive to identifying any such iris region, a respective substitute iris region, containing an iris pattern distinct from the identified iris pattern to avoid identifying the subject within the image, is determined and the identified iris region is replaced with the substitute iris region in the original image.

A method for verifying a person's identity includes receiving a registration request from an electronic device, the request including identifying information associated with a presumed identity of a person and captured metadata indicative of a timing of user inputs entered to the electronic device by the person during a session associated with the request, querying one or more trusted databases to obtain background data item(s) associated with the presumed identity, receiving, from a biometric reader, biometric data item(s) captured from the person during the session, storing a data record associating the identifying information, captured metadata, background data item(s), and biometric data item(s), calculating a hash as a function of the identifying information, captured metadata, background data item(s), biometric data item(s), storing the hash in a block of a blockchain, deriving a score from the captured metadata and background data item(s), and generating an embeddable digital badge based on the score.