Abstract: Authentication of electronic document is based on multiple digital signatures incorporated into a blockchain. Structured data, metadata, and instructions may be hashed to generate the multiple digital signatures for distribution via the blockchain. Any peer receiving the blockchain may then verify an authenticity of an electronic document based on any one or more of the multiple digital signatures incorporated into the blockchain.

Abstract: A personal blockchain is generated as a cloud-based software service in a blockchain environment. The personal blockchain immutably archives usage of any device, perhaps as requested by a user. However, some of the usage may be authorized for public disclosure, while other usage may be designated as private and restricted from public disclosure. The public disclosure may permit public ledgering by still other blockchains, thus providing two-way public/private ledgering for improved record keeping. Private usage, though, may only be documented by the personal blockchain.

Abstract: A personal blockchain is generated as a cloud-based software service in a blockchain environment. The personal blockchain immutably archives particular usage of any device, perhaps as requested by a user. The user may thus peruse past or historical usage (such as message logs) and individually select historical messages that are desired for a blockchain recordation in the personal blockchain. Moreover, the usage may be publicly ledgered by still other blockchains, thus providing two-way ledgering for improved record keeping.

Abstract: Authentication of electronic document is based on multiple digital signatures incorporated into a blockchain. Structured data, metadata, and instructions may be hashed to generate the multiple digital signatures for distribution via the blockchain. Any peer receiving the blockchain may then verify an authenticity of an electronic document based on any one or more of the multiple digital signatures incorporated into the blockchain.

Abstract: Confidential, secret data may be shared via one or more blockchains. Mortgage applications, medical records, financial records, and other electronic documents often contain social security numbers, names, addresses, account information, and other personal data. A secret sharing algorithm is applied to any secret data to generate shares. The shares may then be integrated or written to one or more blockchains for distribution.

Abstract: Data verification in federate learning is faster and simpler. As artificial intelligence grows in usage, data verification is needed to prove custody and/or control. Electronic data representing an original version of training data may be hashed to generate one or more digital signatures. The digital signatures may then be incorporated into one or more blockchains for historical documentation. Any auditor may then quickly verify and/or reproduce the training data using the digital signatures. For example, a current version of the training data may be hashed and compared to the digital signatures generated from the current version of the training data. If the digital signatures match, then the training data has not changed since its creation. However, if the digital signatures do not match, then the training data has changed since its creation. The auditor may thus flag the training data for additional investigation and scrutiny.

Abstract: Data verification in federate learning is faster and simpler. As artificial intelligence grows in usage, data verification is needed to prove custody and/or control. Electronic data representing an original version of training data may be hashed to generate one or more digital signatures. The digital signatures may then be incorporated into one or more blockchains for historical documentation. Any auditor may then quickly verify and/or reproduce the training data using the digital signatures. For example, a current version of the training data may be hashed and compared to the digital signatures generated from the current version of the training data. If the digital signatures match, then the training data has not changed since its creation. However, if the digital signatures do not match, then the training data has changed since its creation. The auditor may thus flag the training data for additional investigation and scrutiny.