Secure cross-blockchain asset movement using photonic quantum computing
Systems and methods for securing a cryptocurrency asset transfer via a cross-blockchain bridge. Methods may include detecting a request to transfer the asset between blockchains and extracting a set of features such as smart contract bytecode from event logs associated with the blockchains and a blockchain bridge. Methods may include using a photonic quantum processor to use i) a long short-term neural network and ii) a neural network to generate machine learning models based on the extracted features to output i) a security risk threshold and ii) a security risk percentage, respectively. When the security risk percentage is below the security risk threshold, the method may permit the execution of a smart contract to allow transfer of the cryptocurrency asset over the blockchain bridge. When the security risk percentage is above the security risk threshold, the method may involve blocking an execution of a smart contract on the blockchain bridge.
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.
2. The method of claim 1 , when the security risk percentage is above the security risk threshold, further comprising sending out an alert notification to the nodes in the first blockchain.
3. The method of claim 1 , when the security risk percentage is above the security risk threshold, further comprising sending out an alert notification to the nodes in the second blockchain.
4. The method of claim 1 , when the security risk percentage is above the security risk threshold, further comprising sending out an alert notification to the nodes in the first blockchain and the second blockchain.
5. The method of claim 1 , when the security risk percentage is above the security risk threshold, further comprising sending out an alert notification to the nodes in the blockchain bridge.
6. 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, requesting one or more additional tokens to verify an authenticity of a transfer before executing the smart contract on the blockchain bridge.
7. The method of claim 6 , wherein the additional tokens are received from the second node.
8. The method of claim 6 , wherein the additional tokens are received from the first node.
9. The method of claim 6 , wherein the additional tokens are received from the first node and the second node.
10. The method of claim 6 , wherein the additional tokens are received from an entity related to the blockchain bridge.
11. The method of claim 6 , when the security risk percentage is above the security risk threshold, further comprising sending out an alert notification to the nodes in the first blockchain.
12. The method of claim 6 , when the security risk percentage is above the security risk threshold, further comprising sending out an alert notification to the nodes in the second blockchain.
13. The method of claim 6 , when the security risk percentage is above the security risk threshold, further comprising sending out an alert notification to the nodes in the first blockchain and the second blockchain.
14. The method of claim 6 , when the security risk percentage is above the security risk threshold, further comprising sending out an alert notification to the nodes in the blockchain bridge.