A scheme for securely transferring a patient data file to an intended recipient regardless of a transfer mode selected by a sender. Encryption system executing at the sender device is operative to encrypt each plaintext data line of a file, one by one, using a symmetric key and a starting IV that is incremented per each line, resulting in corresponding ciphertext lines added to an encrypted file. A hash is generated based on the encrypted file. An encrypted header containing the symmetric key, starting IV and the hash is generated using a public key of the recipient, which is appended to the encrypted file. The encrypted header and associated encrypted file are transmitted to the recipient in any manner. Upon receipt, the recipient decrypts the encrypted header using a private key to obtain the symmetric key, starting IV and the hash, which are used by the recipient to validate and decrypt the encrypted file on a line-by-line basis.

A computer-implemented method of auditing drug supply chain data gathered from a distributed ledger is disclosed. The method includes receiving a population of drug product records from the distributed ledger. The method includes receiving a first set of drug product criteria. The method includes determining a weighted probability for one or more drug product records of the population of drug product records. The method includes generating a randomized first subset of drug product records from the population of drug product records based on the weighted probability of the one or more drug product records. Other methods, systems, and the like for unbiased drug selection for audit are also disclosed.

Data privacy is a major concern when accessing and processing sensitive medical data. Homomorphic Encryption (HE) is one technique that preserves privacy while allowing computations to be performed on encrypted data. An encoding method enables typical HE schemes to operate on real-valued numbers of arbitrary precision and size by representing the numbers as a series of polynomial terms.

Systems, methods, and computer-readable storage media for receiving, from an issuer, an electronic prescription for a patient, then fulfilling that prescription using a blockchain/distributed ledger verification system. The system receives multiple public keys, combines them, then performs a hash function (or other encryption) on that combination. The resulting output is then transmitted to a pharmacy for prescription fulfillment.

A system for an artificial intelligence synchronized distributed ledger. The system includes a computing device containing a receiving module, the receiving module designed and configured to receive an input from a remote device, parse the input to identify protected and non-protected data contained within the input, transform the protected data into a digitally signed assertion and convert the non-protected into an encrypted datastore. The computing device containing a processing module, the processing module designed and configured to receive the digitally signed assertion from the receiving module, insert the digitally signed assertion into an immutable sequential data structure, receive the encrypted datastore, retrieve at least an input, generate a record utilizing the at least a retrieved input, and perform a first machine-learning process utilizing the at least a retrieved input.

Techniques for enabling the creation of a digital asset representation of physical goods (e.g., luxury items) produced in limited quantities or heirloom-goods associated with restricted ownership rules. Anti-counterfeiting mechanisms are proposed for both classes of goods. The provenance of both classes of goods is traced using cryptography and decentralized ledger technology. For example, mechanisms to restrict ownership of heirloom-goods are proposed based on the combination of the DNA biological fingerprint of the patron who originated the goods and smart contract technology. The goods can be represented as digital tokens on the blockchain, binding manufacturing evidence to the token. For heirloom-goods that have restricted ownership rules, persons seeking to acquire the good via the digital token and smart contract are required to prove that they satisfy the entitlement rules based on a biological relationship to the patron.

A method of authorizing a limited use intravascular device can include determining if the intravascular device is in communication with a clinical system; determining if the intravascular device is authorized for clinical operation without providing the clinical system access to intravascular device data stored on the intravascular device; and providing an authorization signal to the clinical system. An intravascular device can include a flexible elongate member including a sensing component at a distal portion and a connector at a proximal portion, the connector including: a memory component configured to store a parameter value; a processing component; and a charge storage component configured to power the memory component and/or the processing component; wherein the processing component is configured to determine if the flexible elongate member is authorized for clinical operation using the parameter value without providing the parameter value to a clinical system.

Disclosed is a computer-implemented method for establishing a secure connection between two electronic computing devices which are located in a network environment, the two electronic computing devices being a first computing device offering the connection and a second computing device designated to accept the connection, the method comprising executing, by at least one processor of at least one computer, a connection-establishing application for exchanging an information packet between the first computing device and the second computing device comprising a secret usable for establishing the connection, and evaluating a response from the second computing device for establishing the secure connection.

Aspects of the present disclosure provide systems, methods, and computer-readable storage media that support secure training of machine learning (ML) models that preserves privacy in untrusted environments using distributed executable file packages. The executable file packages may include files, libraries, scripts, and the like that enable a cloud service provider configured to provide ML model training based on non-encrypted data to also support homomorphic encryption of data and ML model training with one or more clients, particularly for a diagnosis prediction model trained using medical data. Because the training is based on encrypted client data, private client data such as patient medical data may be used to train the diagnosis prediction model without exposing the client data to the cloud service provider or others. Using homomorphic encryption enables training of the diagnosis prediction model using encrypted data without requiring decryption prior to training.

Techniques for managing encoded communications for medical devices in a clinical environment are provided. Different versions of signal coding libraries are generated for different devices in a communication path. A first signal coding library may be generated using a first signal definition that includes a set of fields. A second signal coding library may be generated using a second signal definition that includes a subset of the fields of the first signal definition, and excludes one or more of the fields of the first signal definition. A message encoded using the first signal coding library may not be completely decodable using the second signal coding library. By selectively deploying the signal coding libraries to different systems, devices, and components in a clinical environment, access to information in message fields can be effectively managed.