Abstract: A member of a group in a blockchain network may generate a public key and a private key, request a blockchain network group certificate, associated with the private key, from a blockchain network certificate authority, and distribute a private key to members of the group.

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: An example operation may include one or more of receiving, via a custodial service, a request to transact with a digital asset owned by a user and temporarily in custody of the custodial service, generating a blockchain transaction comprising an identifier of the digital asset on a blockchain ledger, an identifier of the custodial service, and an identifier of a recipient of the digital asset, signing the blockchain transaction with a key from a trifocal key which proves that the custodial service is authorized to transact with the digital asset on behalf of the user, and storing the signed blockchain transaction on a blockchain ledger.

Abstract: An example operation may include one or more of receiving a request for executing a trade transaction with a digital token, determining to execute an additional verification on the digital token based on one or more of a newness of the digital token and a lack of data on the digital token, querying a blockchain ledger associated with the digital token for one or more additional data attributes of the digital token, and determining whether or not to execute the trade transaction with the digital token based on the one or more additional data attributes of the digital token queried from the blockchain ledger.

Abstract: The processor may collect, from a first peer, a first data set associated with a channel. The channel may include one or more assets associated with a first peer. The channel may link the first peer to a second peer. The processor may analyze the first data set to determine a first status for the one or more assets. The processor may provide the first status of the one or more assets in a viewable channel to the blockchain network.

Abstract: An example operation may include one or more of receiving, by a risk score module, a blockchain transaction proposal, obtaining transaction proposal data, obtaining external data, computing a risk score from the transaction proposal data and the external data, comparing the risk score to a risk score threshold, providing an endorsement decision, based on the comparison, and one of endorsing or rejecting the transaction proposal.

Abstract: An example operation may include one or more of identifying a plurality of instances of a blockchain storage request that have been independently submitted by a plurality of clients, respectively, verifying whether execution content of the plurality of instances of the blockchain storage request match, and in response to verifying the match, storing the blockchain storage request within a block among a hash-linked chain of blocks.

Abstract: Techniques for refinement of data pipelines are provided. An original file of serialized objects is received, and an original pipeline comprising a plurality of transformations is identified based on the original file. A first computing cost is determined for a first transformation of the plurality of transformations. The first transformation is modified using a predefined optimization, and a second cost of the modified first transformation is determined. Upon determining that the second cost is lower than the first cost, the first transformation is replaced, in the original pipeline, with the optimized first transformation.

Abstract: An example operation may include one or more of receiving a data file with off-chain content that originated in a first security domain of a multi-domain blockchain network, verifying that the on-chain and off-chain content satisfies a cross-domain security policy between the first security domain and a second security domain within the multi-domain blockchain network with a different security policy than the first security domain, in response to verifying the on-chain and off-chain content, signing the on-chain portion of the data file with a signature of a cross-domain endorsement peer, transmitting the signed on-chain portion of the data file to an ordering service of the multi-domain blockchain network, and transmitting the off-chain portion of the data file to a cross-domain content controller in the first security domain.

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.