# US 11,907,347 B2 · System for secure verification of authentication data using quantum computing and a distributed server network > Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt - Number: US 11,907,347 B2 - Document ID: US11907347B2 - Status: Granted - Kind: B2 - Application number: 17/352,659 - Filed: 2021-06-21 - Published: 2022-12-22 - Granted: 2024-02-20 - Earliest claimed: 2021-06-21 - Assignees: Bank of America Corporation - Applicants: Bank of America Corporation - Inventors: Obi Reddy Yanamala; Ravi Ranjan Shandilya; Vinay Jaisinghani; Kumaresan Karuppiah; Samson Paulraj - Web page: https://patentgrep.com/patent/US11907347B2 ## CPC - G06F 21/32: using biometric data, e.g. fingerprints, iris scans or voiceprints - G06N 10/00: Quantum computing, i.e. information processing based on quantum-mechanical phenomena - G06N 10/60: Quantum algorithms, e.g. based on quantum optimisation, quantum Fourier or Hadamard transforms - G06N 20/10: using kernel methods, e.g. support vector machines [SVM] - G06F: ELECTRIC DIGITAL DATA PROCESSING (computer systems based on specific computational models G06N) - G06N: COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS ## Abstract A system is provided for secure verification of authentication data using quantum computing and a distributed server network. In particular, the system may store a reference set of authentication data associated with a user within a distributed server database in an encrypted form. Subsequently, when the system receives live set of authentication data associated with the user, the system may, using a quantum authenticator, compare the encrypted live set of authentication data with the encrypted reference set of authentication data for authorization purposes. The system may further comprise a quantum machine learning authorization engine which may track historical data and/or settings associated with the user to model and predict behavior patterns of the user. In this way, the system provides a secure and efficient way to perform authentication and/or authorization of the user. ## Claims ### Claim 1 A system for secure verification of authentication data using quantum computing and a distributed server network, the system comprising: a memory device with computer-readable program code stored thereon; a communication device; and a processing device operatively coupled to the memory device and the communication device, wherein the processing device is configured to execute the computer-readable program code to: receive, from a user, a reference set of authentication data; execute a feature extraction process on the reference set of authentication data to generate reference feature data; encrypt the reference feature data to generate encrypted reference authentication data; store the encrypted reference authentication data within a distributed register; receive, from a second user, a request to execute a user action and a live set of authentication data, wherein the user action comprises a resource transfer; execute the feature extraction process on the live set of authentication data to generate live feature data; encrypt the live feature data to generate encrypted live authentication data; authenticate the user by comparing, using a quantum authenticator, the encrypted live authentication data with the reference authentication data; and authorize, using a quantum machine learning authorization process, the request to perform the user action, wherein authorizing the request to perform the user action comprises: classifying, using a quantum support vector machine algorithm, one or more data points within historical data associated with the user, wherein the historical data comprises historical resource transfer information, the historical resource transfer information comprising a resource amount, a time of execution, a location of execution, source information, and destination information; identifying one or more user-defined settings associated with the user; determining whether the request to perform the user action is consistent with the historical data associated with the user and the one or more user-defined settings associated with the user; and based on determining whether the request to perform the user action is consistent with the historical data associated with the user and the one or more user-defined settings associated with the user, validating the user action. ### Claim 2 (depends on 1) The system according to claim 1, wherein validating the user action comprises permitting the user action to be executed. ### Claim 3 (depends on 1) The system according to claim 1, wherein validating the user action comprises automatically blocking the user action from being executed. ### Claim 4 (depends on 1) The system according to claim 1, wherein authenticating the user comprises: detecting a match between the encrypted live authentication data and the encrypted reference authentication data; and based on detecting the match, identifying the second user as the user. ### Claim 5 (depends on 1) The system according to claim 1, wherein authenticating the user comprises: detecting a mismatch between the encrypted live authentication data and the encrypted reference authentication data; based on detecting the mismatch, identifying the second user is not the user; and automatically blocking the user action from being executed. ### Claim 6 (depends on 1) The system according to claim 1, wherein the reference set of authentication data and the live set of authentication data each comprise biometric identifier data. ### Claim 7 (depends on 6) The system according to claim 6, wherein the feature extraction process comprises identifying and quantifying one or more characteristics of the biometric identifier data. ### Claim 8 A computer program product for secure verification of authentication data using quantum computing and a distributed server network, the computer program product comprising at least one non-transitory computer readable medium having computer-readable program code portions embodied therein, the computer-readable program code portions comprising executable portions for: receiving, from a user, a reference set of authentication data; executing a feature extraction process on the reference set of authentication data to generate reference feature data; encrypting the reference feature data to generate encrypted reference authentication data; storing the encrypted reference authentication data within a distributed register; receiving, from a second user, a request to execute a user action and a live set of authentication data, wherein the user action comprises a resource transfer; executing the feature extraction process on the live set of authentication data to generate live feature data; encrypting the live feature data to generate encrypted live authentication data; authenticating the user by comparing, using a quantum authenticator, the encrypted live authentication data with the reference authentication data; and authorizing, using a quantum machine learning authorization process, the request to perform the user action, wherein authorizing the request to perform the user action comprises: classifying, using a quantum support vector machine algorithm, one or more data points within historical data associated with the user, wherein the historical data comprises historical resource transfer information, the historical resource transfer information comprising a resource amount, a time of execution, a location of execution, source information, and destination information; identifying one or more user-defined settings associated with the user; determining whether the request to perform the user action is consistent with the historical data associated with the user and the one or more user-defined settings associated with the user; and based on determining whether the request to perform the user action is consistent with the historical data associated with the user and the one or more user-defined settings associated with the user, validating the user action. ### Claim 9 (depends on 8) The computer program product of claim 8, wherein validating the user action comprises permitting the user action to be executed. ### Claim 10 (depends on 8) The computer program product of claim 8, wherein validating the user action comprises automatically blocking the user action from being executed. ### Claim 11 (depends on 8) The computer program product of claim 8, wherein authenticating the user comprises: detecting a match between the encrypted live authentication data and the encrypted reference authentication data; and based on detecting the match, identifying the second user as the user. ### Claim 12 (depends on 8) The computer program product of claim 8, wherein authenticating the user comprises: detecting a mismatch between the encrypted live authentication data and the encrypted reference authentication data; based on detecting the mismatch, identifying the second user is not the user; and automatically blocking the user action from being executed. ### Claim 13 (depends on 8) The computer program product of claim 8, wherein the reference set of authentication data and the live set of authentication data each comprise biometric identifier data. ### Claim 14 A computer-implemented method for secure verification of authentication data using quantum computing and a distributed server network, the computer-implemented method comprising: receiving, from a user, a reference set of authentication data; executing a feature extraction process on the reference set of authentication data to generate reference feature data; encrypting the reference feature data to generate encrypted reference authentication data; storing the encrypted reference authentication data within a distributed register; receiving, from a second user, a request to execute a user action and a live set of authentication data, wherein the user action comprises a resource transfer; executing the feature extraction process on the live set of authentication data to generate live feature data; encrypting the live feature data to generate encrypted live authentication data; authenticating the user by comparing, using a quantum authenticator, the encrypted live authentication data with the reference authentication data; and authorizing, using a quantum machine learning authorization process, the request to perform the user action, wherein authorizing the request to perform the user action comprises: classifying, using a quantum support vector machine algorithm, one or more data points within historical data associated with the user, wherein the historical data comprises historical resource transfer information, the historical resource transfer information comprising a resource amount, a time of execution, a location of execution, source information, and destination information; identifying one or more user-defined settings associated with the user; determining whether the request to perform the user action is consistent with the historical data associated with the user and the one or more user-defined settings associated with the user; and based on determining whether the request to perform the user action is consistent with the historical data associated with the user and the one or more user-defined settings associated with the user, validating the user action. ### Claim 15 (depends on 14) The computer-implemented method of claim 14, wherein validating the user action comprises permitting the user action to be executed. ### Claim 16 (depends on 14) The computer-implemented method of claim 14, wherein validating the user action comprises automatically blocking the user action from being executed. ### Claim 17 (depends on 14) The computer-implemented method of claim 14, wherein authenticating the user comprises: detecting a match between the encrypted live authentication data and the encrypted reference authentication data; and based on detecting the match, identifying the second user as the user. ### Claim 18 (depends on 14) The computer-implemented method of claim 14, wherein authenticating the user comprises: detecting a mismatch between the encrypted live authentication data and the encrypted reference authentication data; based on detecting the mismatch, identifying the second user is not the user; and automatically blocking the user action from being executed. ### Claim 19 (depends on 14) The computer-implemented method of claim 14, wherein the reference set of authentication data and the live set of authentication data each comprise biometric identifier data. ### Claim 20 (depends on 19) The computer-implemented method of claim 19, wherein the feature extraction process comprises identifying and quantifying one or more characteristics of the biometric identifier data.