Verizon Patent and Licensing Inc.

Rasmi Ranjan Samal

Ahmed A Khan

Rangesh Sripathi

Abdul Raheem

Mohammed A Qaudeer

Jeaha Yang

David Szol

A system described herein may generate a hash value based on a set of data stored in an off-chain repository. The system may record an association between the set of data and the hash value to a blockchain system, receive a query from a client device, determine that the query is associated with the set of data, output a response to the query based on the set of data. The response may include the hash value. The system may authenticate the query (e.g., the client device) using one or more suitable authentication mechanisms, thus securing access to the set of data. The client device may verify the set of data based on determining that the hash value included in the response matches the hash value recorded to the blockchain system as being associated with the set of data.

Systems and methods for scalable off-chain storage of blockchain-secured data

A system described herein may identify a plurality of records recorded to a blockchain, and may identify a particular record of the plurality of records that includes a particular indicator that the particular record is associated with a particular event. The particular indicator may indicate a type of off-chain event. The system may perform, based on identifying the particular record that is associated with the particular event, one or more off-chain actions associated with the particular event. The performed off-chain event may be the indicated type, out of a plurality of possible types of events to perform. The system may record, to the blockchain, an indication that the one or more off-chain actions associated with the particular event have been performed. The event may include an identifier, which the system may also record to the indication that the one or more off-chain actions have been performed.

Systems and methods for off-chain action orchestration using blockchain events

A system described herein may utilize artificial intelligence/machine learning ('AI/ML') or other suitable techniques to automatically identify blocks added to or proposed to be added to a blockchain, with conflicting and/or otherwise incompatible information, and to automatically remediate the blockchain based on the identified conflict and/or incompatibility. The model may associate different types of conflicts and/or incompatibilities with different types of remedial measures. The remedial measures may include the rejection of a proposed block, recording a new block that takes precedence or priority over a previously recorded block, or other suitable remedial measures.

Systems and methods for AI/machine learning-based blockchain validation and remediation

A system described herein may generate a group of distributed ledgers that are each associated with a respective set of ledger parameters, receive a data item that is associated with a set of attributes, identify a distributed ledger that is associated with ledger parameters that meet the set of attributes, and record the data item to the distributed ledger that is associated with ledger parameters that meet the particular set of attributes. The system may determine that a set of archival parameters, associated with a particular distributed ledger, have been met; and may remove the particular distributed ledger from the group of distributed ledgers based on determining that the set of archival parameters, associated with the particular distributed ledger, have been met. Nodes that maintain the group of distributed ledgers may remove ledger data, associated with the removed distributed ledger, from one or more storage resources associated with the nodes.

Systems and methods for distributed ledger archiving and size management

A system described herein may receive a proposed interaction with a distributed ledger, including a reference to a value that has been previously recorded to the distributed ledger. The system may attempt to obtain the value from an associated cache. If the value is unable to be obtained from the cache, the system may communication with an external device via a network to obtain the value. The system may execute the proposed interaction based on the obtained first value. The system may receive a finalized block based on the executed interaction, and may update the cache based on one or more values included in the finalized block.

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Hyderabad Telangana, India

Rasmi Ranjan Samal