US 12,131,329 B2
Secure cross-blockchain asset movement using photonic quantum computing
Shailendra Singh, Maharashtra (IN)
Assigned to Bank of America Corporation, Charlotte, NC (US)
Filed by Bank of America Corporation, Charlotte, NC (US)
Filed on Mar. 21, 2023, as Appl. No. 18/124,063.
Prior Publication US 2024/0320676 A1, Sep. 26, 2024
Int. Cl. G06Q 20/40 (2012.01); G06Q 20/02 (2012.01); G06Q 20/38 (2012.01); G06N 10/00 (2022.01); G06N 20/00 (2019.01)
CPC G06Q 20/4016 (2013.01) [G06Q 20/02 (2013.01); G06Q 20/389 (2013.01); G06N 10/00 (2019.01); G06N 20/00 (2019.01)] 14 Claims
OG exemplary drawing
 
1. A method for securing a cryptocurrency transfer via a cross-blockchain bridge, the method comprising:
detecting a request to transfer a cryptocurrency asset between a first node in a first blockchain and a second node in a second blockchain;
extracting a first set of features from a first blockchain event log associated with the first blockchain, the first set of extracted features comprising smart contract bytecode associated with the first blockchain event log;
extracting a second set of features from a second blockchain event log associated with the second blockchain, the second set of extracted features comprising smart contract bytecode associated with the second blockchain event log;
extracting a third set of features from a blockchain bridge event log associated with a blockchain bridge, the third set of extracted features comprising smart contract bytecode associated with the blockchain bridge event log;
at a photonic quantum processor:
using a long short-term neural network, generating a first machine learning model based at least in part on the first set of extracted features, the second set of extracted features, and the third set of extracted features;
based on the first machine learning model, outputting a security risk threshold associated with the request to transfer the cryptocurrency asset;
at the photonic quantum processor:
using a second neural network, generating a second machine learning model based at least in part on the first set of extracted features, the second set of extracted features, and the third set of extracted features, the second machine learning model comprising a transfer profile knowledge graph;
based on the transfer profile knowledge graph, outputting a security risk percentage associated with the request to transfer the cryptocurrency asset;
in response to the outputs from the long short-term neural network and the second neural network:
when the security risk percentage is below the security risk threshold, permitting an execution of a smart contract on the blockchain bridge, the executing comprising:
burning a first cryptocurrency token associated with the cryptocurrency asset at the first node in the first blockchain;
minting a second cryptocurrency token associated with the cryptocurrency asset at the second node in the second blockchain;
when the security risk percentage is above the security risk threshold, blocking an execution of a smart contract on the blockchain bridge.