A collecting method records medical transaction declarations by: inputting private information of a patient; requiring two immediate and simultaneous fingerprints, one from each of two persons; displaying prompts for camera photographic images; acquiring the camera photographic images; recording a response through an apparatus display and user-selectable response; prompting for biometric reader activation; recording biometric fingerprints from each of the two persons on each of two physical reader devices, respectively; time-stamping a first fingerprint and a second fingerprint and electronically determining that the two fingerprints are recorded within a time period; computing an electronic decision about the physical proximity of the two persons based upon at least a time-stamp of the first fingerprint and a time-stamp of the second fingerprint; merging biometric signatures from the two persons into an electronic agreement; generating a signed electronic agreement; and outputting the signed electronic agreement to permanent storage to memorialize the medical transaction declaration.

In a personal searching-purpose ID (511), a personal encryption ID (512) and encrypted personal information (513) stored in a personal information storage unit (51), a disclosure range of personal information is embedded. Also, in a medical searching-purpose ID and a medical encryption ID stored in a medical data storage unit, a disclosure range of medical data is embedded. A search query generation unit generates a search query Q by encrypting a search anonymous ID subject to searching acquired from a user with attribution information of the user embedded. Then, a searching unit executes confidential searching on the personal searching-purpose ID (511) and a pathological searching-purpose ID (521), using the search query Q. The searching unit outputs a searching result acquired based on the attribution information of the user, the disclosure range of personal information and the disclosure range of medical data.

An inventive method for validating an end user device for use with a medical application. A medical application and a validation application are received in the end user device and the validation application is then executed, which includes: (i) determining the hardware and software environment of the end user device; (ii) providing a validation process compatible with the hardware and software environment; (iii) executing a test mode of the medical application; (iv) running the validation process during the test mode; and (v) determining from running the validation process whether the medical application is compatible with the end user device. When the medical application is determined to be compatible with the end user device, a validation report is generated and stored in the end user device and/or a server. When the medical application is determined to be incompatible with the end user device, the medical application is at least partially blocked.

Multivariate encryption systems and methods are provided herein. An example method includes receiving a multivariate input set that includes a plurality of sensitive data objects arranged according to a record template, encrypting the multivariate input set into an encrypted representation, receiving a request for at least a portion of the plurality of sensitive data objects, extracting the at least a portion of the plurality of sensitive data object from the encrypted representation and generating a response message that includes only the at least a portion of the plurality of sensitive data objects that were extracted from the encrypted representation.

A proof of provenance system receives database logs from an existing system that does not natively provide data provenance verification. The system produces a local representation of the database (or a portion thereof). The system periodically or in response to another triggering event flattens the local representation of the database to generate an aggregated slice, which is stored in an aggregated slice store. A reduced representation of the aggregated slice (e.g., a hash or checksum) is determined and appended to a distributed ledger, such as a blockchain. The provenance of data from the existing system can then be verified by redetermining the reduced representation and comparing it to the version appended to the distributed ledger.

Electronic network include multiple users. Each user operates Wallet software application on his/her endpoint devices (special purpose, computer or smartphone). Each Wallet integrates with Cloud-based Identification-as-a-Service(s) (IDaaS) In context of present inventionIDaaS provides real-time, multi-factor, malware-resilient, context-sensitive Strong Identification-as-a-Service of the user and enables Cryptographic Keys Management of the Wallet. Each Wallet provides various Cryptographic functionalities. Each Wallet may be connected with multiple centralized Marketplace software applications, thus allowing these Cryptographic functionalities to interact with specific Marketplace software application. Each Wallet may be connected with multiple decentralized peer-to-peer software applications, thus allowing these Cryptographic functionalities to interact with specific peer-to-peer software application. These software applications may include Information Technology, Financial, Manufacturing, Retail, Insurance, Government, Healthcare and other verticals of Global Economy. The present invention prevents Bad Actors from using or attacking these applications. The present invention also enables Identification of participants of transactions recorded on Blockchain.

Described is a method and system for the secure management and verification of prescriptions allowing patients, doctors and dispensers to access prescriptions as directed by patients. An example method may include generating a code vector including a series of authentication codes, storing at least one of the authentication codes on a peripheral device, maintaining an indication of a next expected authentication code from the code vector, allowing prescription creation by a user when the peripheral device is detected and determined to be an authorized device, and that the authentication code provided from the peripheral device matches the next expected authentication code, storing a prescription associated with a patient having a patient PIN, wherein the prescription is provided by the user, generating a plurality of refill verification codes associated with the prescription, and authorizing dispensing responsive to receipt of one of the plurality of refill verification codes and the patient PIN.

Described herein are a secure system for sharing private data and related systems and methods for incentivizing and validating private data sharing. In some embodiments, private data providers may register to selectively share private data under controlled sharing conditions. The private data may be cryptographically secured using encryption information corresponding to one or more secure execution environments. To demonstrate to the private data providers that the secure execution environment is secure and trustworthy, attestations demonstrating the security of the secure execution environment may be stored in a distributed ledger (e.g., a public blockchain). Private data users that want access to shared private data may publish applications for operating on the private data to a secure execution environment and publish, in a distributed ledger, an indication that the application is available to receive private data. The distributed ledger may also store sharing conditions under which the private data will be shared.

Provided are methods and systems for performing a secure machine learning analysis over an instance of data. An example method includes acquiring, by a client, an homomorphic encryption scheme, and at least one machine learning model data structure. The method further includes generating, using the encryption scheme, at least one homomorphically encrypted data structure, and sending the encrypted data structure to at least one server. The method includes executing a machine learning model, by the at least one server based on the encrypted data structure to obtain an encrypted result. The method further includes sending, by the server, the encrypted result to the client where the encrypted result is decrypted. The machine learning model includes neural networks and decision trees.

A platform may receive, from a user device, a request for a status of an animal, wherein the request includes animal identification information associated with the animal. The platform may identify, based on receiving the request, an animal record identifier associated with the animal. The platform may verify that an entity associated with the user device is authorized to obtain the status of the animal, wherein the entity is one of a plurality of entities that are authorized to obtain the status of the animal. The platform may identify, based on verifying that the entity is associated with the user device, blocks of a blockchain that include the animal record identifier. The platform may determine the status of the animal from animal records associated with the animal, wherein the animal records are included within the blocks. The platform may provide, to the user device, the status of the animal.