Abstract: A client computer may split a process into sub-processes, send each sub-processes to a different group of peers in a blockchain network, wherein each group has at least one peer from each essential organization in the blockchain network, receive processed sub-transactions from the peers in the blockchain network, validate each sub-transaction, and validate the transaction based on the validation of all sub-transactions, wherein all sub-transaction must be valid for the transaction to be valid.

Abstract: Systems, methods, and computer programming products for detecting, clearing and/or separating potentially tainted digital assets entering a digital network, providing an avenue to satisfy regulatory requirements and ensure digital asset trading is uninterrupted due to the presence of tainted assets. Specialized nodes of the blockchain network intercept incoming transactions and routes the digital assets to a clearing house for analysis, processing and separation of potentially tainted assets. The clearing house uses a plurality of techniques to track, trace and analyze digital assets using techniques provided by the blockchain network or utilizing one or more service providers. Cleared assets are processed and channeled from the clearing house to the wallets or addresses designated by the transaction information and assets with high potential for being tainted are placed within a special wallet for additional clearance and regulatory scrutiny.

Abstract: A system and related method coordinate data and transactions between an enterprise transaction system (ETS) of an enterprise and a blockchain network (BN). A coexistence mediator intercepts an ETS transaction comprising ETS transaction information (ETS-TI) associated with an enterprise. The ETS-TI includes transaction context information (ETS-TCI) regarding the ETS transaction. The system determines an ETS transaction context from the ETS-TCI. Responsive to determining the ETS transaction context represents an in-flight ETS transaction, rerouting, the coexistence mediator reroutes the transaction from the ETS to the BN. The rerouting comprises converting the ETS-TI to BN transaction information (BN-TI), and interfacing with the BN to record a processed BN transaction as a transaction record. The coexistence mediator, upon recording the BN transaction, provides a new BN-TI associated with the BN transaction. The new BN-TI comprises a BN transaction id.

Abstract: An approach for blockchain transaction processing using generative cryptograms for bi-lateral and Multi-lateral transactions may be provided. The approach may include, the use of decentralization ledger storage, negating the need of repetitive storage while preserving the need for data redundancy. A generative cryptogram may provide verification of processed blocks and file handles or storage address schemes of the ledger storage. The approach creates a cryptogram which is added to transaction processing, post processing and commits to the ledger. In the approach, the cryptogram is the only version of storage pointer and is utilized in subsequent transaction processing without the need for extensive compute and latest cryptogram is all that would be needed for transaction processing.

Abstract: A node in a blockchain network may generate a secret information proof, generate a private/public key pair, encrypt the secret information proof with the private/public key pair, and submit the proof to a blockchain network.

Abstract: An example operation may include one or more of creating, by a blockchain user of a blockchain network, a world state checkpoint transaction requesting world state validation, endorsing, by one or more endorser nodes or peers, the world state checkpoint transaction, transferring endorsements to the blockchain user, recording, by an orderer node or peer, the endorsed world state checkpoint transaction into a block, validating and committing all transactions in the block, calculating and signing a hash of a current world state, by all blockchain nodes or peers of the blockchain network, and verifying, by the blockchain user, world state integrity from the calculated and signed hashes of the current world state.

Abstract: A contribution evaluation method, system, and computer program product that evaluates the contribution of each participant-computing device in the federated learning scheme based upon the quality of model updates received from the participant, measured by the accuracy improvement of FL model with applying the participant's model updates.

Abstract: An example operation may include one or more of receiving a request which identifies a data value, reading, from a distributed blockchain storage, one or more data other data values that are related to the identified data value and which are previously stored thereon, determining whether the identified data value satisfies one or more compliance attributes based on the one or more other data values, and generating an output based on the determination.

Abstract: Systems, methods, and computer programming products leveraging the use of machine learning, cryptographic keys and blockchain technology for validating blockchain transactions. The disclosed systems, methods and products improve detection of malicious cyberattacks and fraud, while reducing occurrences of falsely invalidated transactions and improving overall blockchain security in both permissioned and permissionless blockchain networks. Classifiers are trained using machine learning and other classification techniques by building a transaction history to learn how to identify suspicious transactions on the blockchain. In permissionless and order-execute models of permissioned blockchains, cryptographic keys are publicly registered to guardians residing out of band, who may co-sign requests and override or resubmit transactions marked as suspicious by the classifiers.

Abstract: An example operation may include one or more of receiving, via a first blockchain peer, a request to verify an identity of a user, performing, via the first blockchain peer, an identity validation of the user via a know your customer (KYC) service provider of a blockchain network, determining whether a digital identity of the user has been previously stored by another blockchain peer on a blockchain of the blockchain network, in response to a determination that the digital identity of the user has not been stored on the blockchain, creating a non-fungible token (NFT) that identifies the user, and appending information about the identity validation of the user to a structure of the NFT and storing the NFT in a block of the blockchain.

Abstract: An example operation may include one or more of retrieving decentralized identifiers (DIDs) of a plurality of blockchain peers included within a blockchain network, generating a blockchain declarative descriptor (BDD) which uniquely identifies the blockchain network, where the BDD comprises a machine-readable data file with a first field includes the retrieved DIDs of the blockchain network, a second field including signature data of the plurality of blockchain peers, and a third field including metadata, and transmitting the generated BDD to a blockchain network registry.

Abstract: A computer-implemented method and a computer system are disclosed for generating and executing a software appliance comprising the steps of receiving a work request comprising metadata which indicates processing conditions for a computer processing task to be performed; determining a determined processing environment, depending on the metadata included in the work request; selecting one or more software container templates, depending on the metadata included in the work request; generating the software appliance for the determined processing environment, using the one or more selected software container templates; and deploying the software appliance for executing the software appliance on a processing computer system of the determined processing environment.

Abstract: A node in a blockchain network may generate a key for a first ring, wherein the key unlocks a first collection of data, defining a second ring including a second node of a second organization, derive a second key for a second collection of data, wherein the first key and the second key access the second collection of data, and distributing the second key to the second node.

Abstract: A node in a blockchain network may receive an event initiation for a first digital corollary of a first physical asset, receive conditional data related to the first digital corollary, detecting, by the node, a link to a second digital corollary, prompt a simulation of the second digital corollary, receive an outcome of the simulation, and determine an executable action for the second digital corollary.

Abstract: A quality determination method, system, and computer program product that includes performing a dimensionality reduction on a high-dimensional dataset to form a dimensional-reduced dataset and determining, using a machine learning tool executed on a computing device, a quality of the dimensional-reduced dataset via a review of an extracted feature extracted from the dimensional-reduced dataset.

Abstract: A processor may segment a media key block into two or more subsets. Each of the two or more subsets may be respectively associated with a particular group of receivers, and each receiver of the particular group of receivers may be in a blockchain network. The processor may receive, from a first receiver, a request for permission to process the media key block. The processor may identify which of the two or more subsets that the first receiver is associated. The processor may provide a media key block value to the first receiver.

Abstract: An example operation may include one or more of establishing a communication channel between a sending system and a receiving system, executing an oblivious transfer protocol between the sending system and the receiving system via the established communication channel, wherein the oblivious transfer protocol provides the receiving system with a functional encryption key based on a data vector of the receiving system without the sending system learning the data vector, committing to the functional encryption key using a cryptographic commitment and signing the functional encryption key commitment with a digital key of the receiving system, and storing the signed functional encryption key commitment to a blockchain.

Abstract: An example operation may include one or more of receiving a request for storage at a blockchain network, attaching, via a blockchain node, a verifiable credential created by a self-sovereign identity (SSI) network to a blockchain transaction associated with the request, where the verifiable credential includes a claim of the blockchain node and a proof of the SSI network that created the verifiable credential, transmitting the blockchain transaction and the attached verifiable credential to one or more other blockchain nodes, and storing the blockchain transaction and the attached verifiable credential via a data block on the blockchain.

Abstract: A node in a blockchain network may receive an event initiation for a digital corollary, receive conditional data related to the digital corollary, invoke a smart contract for the digital corollary with instructions to retrieve and run an asset decay smart module, receive an asset decay smart module from an asset decay smart module repository, and process the asset decay smart module with the conditional data to determine an asset decay.

Abstract: Mechanisms for performing intelligent federated machine learning (ML) model updates are provided. A plurality of ML model updates, and a plurality of dataset sketch commitment data structures (sketches), are received from a plurality of participant computing systems. Each sketch provides statistical characteristics of a corresponding local dataset used by a corresponding participant to train a local ML model. A potentially malicious participant identification operation is performed based on an analysis of the plurality of sketches to identify one or more potentially malicious participants based on differences in sketches. ML model updates received from participant computing systems identified as potentially malicious participants are discarded to thereby generate a modified set of updates. The federated ML computer model is updated based on the modified set of updates.