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: 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 identifying a digital token issued via a blockchain, determining an asset that is linked to the digital token, a current custodian of the asset that is linked to the digital token, and a risk value associated with the asset based on attributes of the asset, generating a graph that comprises a path between a user that owns the digital token and the current custodian of the asset, embedding the graph within a field of a template and embedding the risk value within a second field of the template to generate a filled-in template, and displaying the filled-in template within a user interface.

Abstract: An example operation includes one or more of transferring, via a blockchain, a digital value from a sender to a receiver, the digital value representing an off-chain transfer of value, monitoring a message flow between the sender and the receiver, detecting a settlement of the off-chain transfer of value based on message content within messages of the message flow, and returning, via the blockchain, the transferred digital value from the receiver to the sender based on the detected settlement.

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: 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 method, system and computer program product for autonomic caching in an IMDG has been provided. A method for autonomic caching in an IMDG includes receiving from a client of the IMDG a request for a primary query in the IMDG. The method also includes associating the primary query with a previously requested sub-query related to the primary query. Finally, the method includes directing the sub-query concurrently with a directing of the primary query without waiting to receive a request for the sub-query from the client. In this way, the method can proactively predict a receipt of the request for a sub-query following a request for a primary query prior the actual receipt of the request for the sub-query.

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: A node in a blockchain network may create a mapping scheme operation header for a subsequent operation, identify a first preceding operation in a first preceding block, the first preceding operation linked to the subsequent operation, and include a location of the first preceding block in the mapping scheme operation header for the operation proposal.

Abstract: A first neural network can be trained to approximate a state-action value function to estimate an expected cumulative return for an agent to perform an action in a given state, the agent being an autonomous reinforcement learning agent running on the processor. A second neural network can be trained to generate a simulated experience, the second network trained to predict a simulated state at a next time step after performing a given action, the second neural network being trained using real experience in a real environment. The first neural network is trained based on the simulated experience and a real experience from a real environment. A selected action selected by the second neural network given a current state of the real environment can be performed. The agent can explore an action space by uniformly sampling an action from all possible remaining action-state space combinations and performing the sampled action.

Abstract: A graph neural network can be built and trained to predict a risk of an entity. A multi-relational graph network can include a first graph network and a second graph network. The first graph network can include a first set of nodes and a first set of edges connecting some of the nodes in the first set. The second graph network can include a second set of nodes and a second set of edges connecting some of the nodes in the second set. The first set of nodes and the second set of nodes can represent entities, the first set of edges can represent a first relationship between the entities and the second set of edges can represent a second relationship between the entities. A graph convolutional network (GCN) can be structured to incorporate the multi-relational graph network, and trained to predict a risk associated with a given entity.

Abstract: An example operation may include one or more of receiving an asset from an asset owner, initiating an integrity of the asset and entering the asset into a primary chain of genesis, signing the asset and locking the asset in the primary chain of genesis, manifesting the asset as a linked asset in a derivative chain of genesis, detecting a timeout of the asset in the primary chain of genesis, ending a life cycle of the asset in the primary chain of genesis, and creating a new asset in the derivative chain of genesis based on the asset.

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 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: 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: A node in a blockchain network may initiate a non-fungible token identity, establish a profile for the non-fungible token identity, receive reputation data related to the non-fungible token identity, determine, based on the reputation data, a reputation score, append the non-fungible token identity with the reputation score as a non-fungible token metadata tag, and upload the non-fungible token identity and the metadata tag to an ID repository.

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 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.