US 12,602,560 B1 · QR code verification engine

receiving, by a QR code generation system, input data for encoding into a QR code, wherein the input data comprises transaction details, authentication credentials, or access control parameters associated with a registered user account;

generating, by the QR code generation system, a visible QR code encoding the input data;

embedding, by a security module of the QR code generation system, a hidden security layer within the QR code using steganographic encoding or invisible watermarking, wherein the hidden security layer comprises encrypted metadata corresponding to the input data and an encryption key unique to the generated QR code;

encrypting, by the security module, the hidden security layer using asymmetric cryptographic techniques, wherein a public-private key pair is used to encrypt and decrypt the hidden security layer to ensure that only the verification server can validate the QR code;

storing, by a verification server, a record of the QR code including the input data, the hidden security layer, the encryption key, and a cryptographic hash of the QR code, wherein the encryption key is associated with the registered user account;

receiving, by a QR code scanning device, a scanned QR code from a user interaction;

extracting, by the QR code scanning device, the input data from the scanned QR code and decoding, by the security module, the hidden security layer embedded within the scanned QR code using the corresponding encryption key;

validating, by the verification server, the scanned QR code by comparing the extracted input data and the decoded hidden security layer with the corresponding stored record;

determining, by the verification server, whether the cryptographic hash of the scanned QR code matches the stored cryptographic hash, thereby detecting unauthorized modifications or tampering;

analyzing, by an AI-powered tamper detection module comprising a machine learning model, the scanned QR code for anomalies indicative of fraudulent alterations by extracting features from the scanned QR code, predicting an anomaly score using the machine learning model, and determining if the anomaly score exceeds a predefined threshold, wherein the anomalies include pixel distortions, metadata inconsistencies, or unexpected steganographic modifications;

determining, by the AI-powered tamper detection module, whether the scanned QR code exhibits a tampering probability exceeding the predefined threshold, and flagging the scanned QR code as suspicious when the threshold is exceeded;

determining, by a dynamic QR code engine, whether the scanned QR code is a dynamically generated QR code and verifying, by the verification server, whether the scanned QR code remains valid based on a predefined expiration time, rotation schedule, or user-specific conditions;

determining, by the verification server, whether the scanned QR code is associated with a transaction exceeding a predefined risk threshold, and initiating, by the verification server, an additional security measure comprising a secondary biometric authentication request when the predefined risk threshold is exceeded;

transmitting, by the verification server, a biometric authentication request to a user device, wherein the biometric authentication request requires the user to authenticate using fingerprint recognition, facial recognition, or voice authentication before validating the scanned QR code;

receiving, by the verification server, a result of the biometric authentication request and storing, by the centralized QR code registry, a record of the biometric authentication attempt including whether the authentication was successful or failed;

transmitting, by the verification server, a push notification to the user device requesting confirmation of the scanned QR code's intended action, wherein the push notification contains validation details associated with the QR code;

receiving, by the verification server, a user approval or rejection of the scanned QR code through a secure authentication process on the user device;

preventing, by an access control module, execution of an action associated with the scanned QR code when the verification server determines that the cryptographic hash does not match, the AI-powered tamper detection module flags the QR code as suspicious, the user rejects the push notification request, or the biometric authentication request fails;

validating, by a browser plugin security module, a QR code encountered in an online environment, wherein the browser plugin security module scans the QR code embedded in a digital document, email, or webpage and transmits the scanned QR code to the verification server for authentication prior to user interaction;

determining, by the browser plugin security module, whether the scanned QR code is embedded in an email and scanning, by the verification server, metadata associated with the email to determine whether the email originates from a trusted sender before validating the QR code;

determining, by a financial transaction processor, whether the scanned QR code corresponds to a financial transaction, verifying, by the verification server, compliance of the financial transaction with applicable jurisdictional regulations, and processing, by the financial transaction processor, the payment only when the verification server confirms the authenticity of the QR code;

verifying, by an offline authentication module, a scanned QR code in an offline environment using an encrypted metadata validation process, wherein the offline authentication module extracts and decodes the embedded security layer from the scanned QR code without requiring network connectivity;

determining, by a contextual security module, whether the scanned QR code meets predefined contextual security criteria, wherein the contextual security criteria include geographic location, user identity, device fingerprinting, or access control rules;

logging, by a centralized QR code registry, validation results and security alerts related to the scanned QR code, wherein the centralized QR code registry maintains a record of authenticated QR codes, security incidents, and fraud detection metrics;

analyzing, by a behavioral analysis engine, historical QR code interaction data of a user, determining, by the behavioral analysis engine, whether the scanned QR code interaction deviates from expected behavioral patterns, and flagging the scanned QR code as suspicious when the deviation exceeds a predefined threshold;

updating, by the behavioral analysis engine, a dynamic fraud risk score associated with the user based on repeated interactions with QR codes, and modifying, by the verification server, the security requirements for future QR code interactions based on the fraud risk score;

generating, by the verification server, a security alert when the scanned QR code is determined to be tampered, expired, unregistered, suspicious based on behavioral analysis, or rejected by the user, and transmitting, by the verification server, the security alert to a security monitoring system or the user device;

and

wherein the execution of any action associated with the scanned QR code is permitted only when the verification server confirms the authenticity of the QR code, the AI-powered tamper detection module does not detect anomalies, the cryptographic hash matches the stored hash, the push notification request is approved by the user, the biometric authentication request is successful, and the contextual security criteria are satisfied.

QR code verification engine

Life of this patent

QR code verification engine

Life of this patent

Abstract

Claims20