# US 12,602,462 B2 · Artificial-intelligence-enabled authentication based on user metadata > Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt - Number: US 12,602,462 B2 - Document ID: US12602462B2 - Status: Granted - Kind: B2 - Application number: 18/490,031 - Filed: 2023-10-19 - Published: 2025-04-24 - Granted: 2026-04-14 - Earliest claimed: 2023-10-19 - Assignees: Mastercard Technologies Canada Ulc - Applicants: Mastercard Technologies Canada Ulc - Inventors: Kyle Williams; Jonathan McGrandle; Matthew Melnik - Web page: https://patentgrep.com/patent/US12602462B2 ## CPC - G06F 21/32: using biometric data, e.g. fingerprints, iris scans or voiceprints - G06F 21/45: Structures or tools for the administration of authentication - G06N 5/022: Knowledge engineering; Knowledge acquisition - G06N 20/00: Machine learning - G06F 2221/2131: Lost password, e.g. recovery of lost or forgotten passwords - G06F: ELECTRIC DIGITAL DATA PROCESSING (computer systems based on specific computational models G06N) - G06N: COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS ## Abstract A system includes memory hardware configured to store instructions and one or more electronic processors configured to execute the instructions. The instructions include logging historical behavioral biometric metadata from one or more computing platforms, generating a user profile based on the logged historical behavioral biometric metadata, receiving an authentication request from a client computing platform, providing the first behavioral biometric metadata and the user profile to a trained machine learning model to generate a biometric match, generating a positive control signal in response to a positive biometric match, sending the positive control signal to the client computing platform, updating the historical behavioral biometric metadata with the first behavioral biometric metadata, and retraining the trained machine learning model using the updated historical behavioral biometric metadata. The authentication request includes first behavioral biometric metadata. ## Claims ### Claim 1 A system including: memory hardware configured to store instructions and one or more electronic processors configured to execute the instructions, wherein the instructions include: logging historical behavioral biometric metadata from one or more computing platforms; generating a user profile based on the logged historical behavioral biometric metadata; receiving an authentication request from a client computing platform, wherein the authentication request includes first behavioral biometric metadata comprising keystroke dynamics features including a dwell time and a flight time; providing the first behavioral biometric metadata and the user profile to a trained machine learning model to generate a biometric match; generating a positive control signal in response to a positive biometric match; sending the positive control signal to the client computing platform; updating the historical behavioral biometric metadata with the first behavioral biometric metadata; and retraining the trained machine learning model using the updated historical behavioral biometric metadata. ### Claim 2 (depends on 1) The system of claim 1 wherein providing the first behavioral biometric metadata and the user profile to the trained machine learning model to generate the biometric match includes: providing the user profile to the trained machine learning model to generate a reference output; providing the first behavioral biometric metadata to the trained machine learning model to generate a first output; and computing a closeness of the reference output and the first output. ### Claim 3 (depends on 2) The system of claim 2 wherein the instructions include generating the positive biometric match in response to the closeness meeting or exceeding a threshold. ### Claim 4 (depends on 3) The system of claim 3 wherein the instructions include generating a negative biometric match in response to the closeness not meeting or exceeding the threshold. ### Claim 5 (depends on 1) The system of claim 1 wherein the client computing platform is configured to authenticate a password reset request from a user device in response to receiving the positive control signal. ### Claim 6 (depends on 1) The system of claim 1 wherein the client computing platform is configured to authenticate a login request from a user device in response to receiving the positive control signal. ### Claim 7 A computer-implemented method including: logging historical behavioral biometric metadata from one or more computing platforms; generating a user profile based on the logged historical behavioral biometric metadata; receiving an authentication request from a client computing platform, wherein the authentication request includes first behavioral biometric metadata comprising keystroke dynamics features including a dwell time and a flight time; providing the first behavioral biometric metadata and the user profile to a trained machine learning model to generate a biometric match; generating a positive control signal in response to a positive biometric match; sending the positive control signal to the client computing platform; updating the historical behavioral biometric metadata with the first behavioral biometric metadata; and retraining the trained machine learning model using the updated historical behavioral biometric metadata. ### Claim 8 (depends on 7) The method of claim 7 wherein providing the first behavioral biometric metadata and the user profile to the trained machine learning model to generate the biometric match includes: providing the user profile to the trained machine learning model to generate a reference output; providing the first behavioral biometric metadata to the trained machine learning model to generate a first output; and computing a closeness of the reference output and the first output. ### Claim 9 (depends on 8) The method of claim 8 further including generating the positive biometric match in response to the closeness meeting or exceeding a threshold. ### Claim 10 (depends on 9) The method of claim 9 further including generating a negative biometric match in response to the closeness not meeting or exceeding the threshold. ### Claim 11 (depends on 7) The method of claim 7 wherein the client computing platform is configured to authenticate a password reset request from a user device in response to receiving the positive control signal. ### Claim 12 (depends on 7) The method of claim 7 wherein the client computing platform is configured to authenticate a login request from a user device in response to receiving the positive control signal. ### Claim 13 A system including: memory hardware configured to store instructions and one or more electronic processors configured to execute the instructions, wherein the instructions include: logging historical behavioral biometric metadata from one or more computing platforms, generating a user profile based on the logged historical behavioral biometric metadata, receiving an authentication request from a client computing platform, wherein the authentication request includes first behavioral biometric metadata, wherein the first behavioral biometric metadata includes keystroke metadata, wherein the keystroke metadata includes keystroke dynamics metadata, and wherein the keystroke dynamics metadata includes a dwell time and a flight time, providing the first behavioral biometric metadata and the user profile to a trained machine learning model to generate a biometric match, generating a positive control signal in response to a positive biometric match, sending the positive control signal to the client computing platform; updating the historical behavioral biometric metadata with the first behavioral biometric metadata; and retraining the trained machine learning model using the updated historical behavioral biometric metadata.