Abstract: A computer can monitor network traffic on a blockchain computing network. The computer can determine a current level of network congestion on the blockchain computing network. The computer can execute a first machine learning model that predicts a timeseries of future transaction costs based on historical data and the current level network congestion level of the blockchain computing network.  The computer can also execute a second machine learning model to predict a timeseries of future transaction sizes and UTXO types for the distributed ledger-based account based on historical transaction data.  The computer can select one or more UTXOs to use to complete the transaction of the transaction request.  The computer can append a block instance containing an identification of the selected one or more UTXOs to the blockchain to complete the transaction.

Abstract: A computer can monitor network traffic on a blockchain computing network. The computer can determine a current level of network congestion on the blockchain computing network. The computer can execute a first machine learning model that predicts a timeseries of future transaction costs based on historical data and the current level network congestion level of the blockchain computing network. The computer can also execute a second machine learning model to predict a timeseries of future transaction sizes and UTXO types for the distributed ledger-based account based on historical transaction data. The computer can select one or more UTXOs to use to complete the transaction of the transaction request. The computer can append a block instance containing an identification of the selected one or more UTXOs to the blockchain to complete the transaction.

Abstract: A system for controlling access to cryptographic resources is disclosed. The system may receive a request to transfer cryptographic resources between users, including a user identifier and a first cryptographic signature. The system may verify the signature and retrieve an encrypted private key from a key vault using the user identifier. A command to sign the request may be transmitted over a private network to a signature device, which may generate a second cryptographic signature using the decrypted private key. The system may receive the second signature, generate a blockchain operation based on the request and signature, and transmit the operation to a blockchain node for commitment. The system may also handle new account generation, storing encrypted keys in jurisdiction-specific databases, and validating blockchain operations against request parameters.

Abstract: A system for controlling access to cryptographic resources is disclosed. The system may receive a request to transfer cryptographic resources between users, including a user identifier and a first cryptographic signature. The system may verify the signature and retrieve an encrypted private key from a key vault using the user identifier. A command to sign the request may be transmitted over a private network to a signature device, which may generate a second cryptographic signature using the decrypted private key. The system may receive the second signature, generate a blockchain operation based on the request and signature, and transmit the operation to a blockchain node for commitment. The system may also handle new account generation, storing encrypted keys in jurisdiction-specific databases, and validating blockchain operations against request parameters.

Abstract: A computer can monitor network traffic on a blockchain computing network. The computer can determine a current level of network congestion on the blockchain computing network. The computer can execute a first machine learning model that predicts a timeseries of future transaction costs based on historical data and the current level network congestion level of the blockchain computing network. The computer can also execute a second machine learning model to predict a timeseries of future transaction sizes and UTXO types for the distributed ledger-based account based on historical transaction data. The computer can select one or more UTXOs to use to complete the transaction of the transaction request. The computer can append a block instance containing an identification of the selected one or more UTXOs to the blockchain to complete the transaction.

Abstract: A computer can monitor network traffic on a blockchain computing network. The computer can determine a current level of network congestion on the blockchain computing network. The computer can execute a first machine learning model that predicts a timeseries of future transaction costs based on historical data and the current level network congestion level of the blockchain computing network. The computer can also execute a second machine learning model to predict a timeseries of future transaction sizes and UTXO types for the distributed ledger-based account based on historical transaction data. The computer can select one or more UTXOs to use to complete the transaction of the transaction request. The computer can append a block instance containing an identification of the selected one or more UTXOs to the blockchain to complete the transaction.