Systems and methods for monetizing data in decentralized model building for machine learning using a blockchain
AssigneeHewlett Packard Enterprise Development LP
InventorsSathyanarayanan Manamohan, Vishesh Garg, KrishnaPrasad Lingadahalli Shastry
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Abstract
Systems and methods are provided for leveraging blockchain technology in a swarm learning context, where nodes of a blockchain network that contribute data to training a machine learning model using their own local data can be rewarded. In order to conduct such data monetization in a fair and accurate manner, the systems and methods rely on various phases in which Merkle trees are used and corresponding Merkle roots are registered in a blockchain ledger. Moreover, any claims for a reward are challenged by peer nodes before the reward is distributed.
Claims20
A data monetization network node operating in a blockchain network, composing:
- a processor;
- and
- a memory unit operatively connected to the processor including computer code that when executed causes the processor to:
- build a hash tree representing a value of an encrypted raw data record extracted from a machine learning model being trained, and register a corresponding hash tree root in a distributed ledger of the blockchain network;
- submit a claim for a reward represented by a height of the hash tree;
- provide a hash tree proof to another network node in the blockchain network, the hash tree proof verifying the height of the hash;
- and
- calculate an amount of individual data points contributed by the data monetization network node based upon the height of the hash tree, the calculated amount of individual data points comprising a share of a monetization reward for training of the machine learning model.
A data monetization network node operating in a blockchain network, composing:
- a processor;
- and
- a memory unit operatively connected to the processor including computer code that when executed causes the processor to:
- encrypt a raw data record extracted from a machine learning model being trained;
- create and store a non-duplicative value of the encrypted raw data record;
- build a hash tree based on the value, and register a corresponding hash tree root in a distributed ledger of the blockchain network;
- submit a claim for a reward represented by a height of the hash tree;
- calculate a percentage share of a monetization reward for training of the machine learning model;
- register the calculated percentage share of the monetization reward to the distributed ledger;
- and
- upon verification of the calculated percentage share of the monetization reward, receive the calculated percentage share of the monetization reward.
A node participating in a blockchain network, comprising:
- a processor;
- and
- a memory unit operatively connected to the processor including computer code that when executed causes the processor to:
- submit a verification challenge of a reward claim submitted by another network node participating in the blockchain network, the reward claim based on a height of a hash tree;
- receive a hash tree proof from the other blockchain network node, the hash tree proof to verify the height of the hash tree;
- determine an outcome of the verification challenge based on the hash tree proof;
- and
- record the outcome of the verification challenge in a distributed ledger of the blockchain network.
Dependencies are inferred from the claim text.