Multimodal Motion Authentication With Temporal Liveness Verification
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Solution Overview
Problem
Existing user authentication methods, particularly biometrics, are vulnerable to spoof attacks and lack continuous verification, making them insufficient for robust and phishing-resistant security.
Innovation Solution
A multimodal authentication system that combines information capture from various sources, including user and surroundings, using AI to categorize data into object, biometric, lighting, and action categories, generating key instructions for registration and authentication, and employing a temporal authentication module for continuous verification.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If traditional biometric authentication methods are used, then user convenience is improved, but security against spoof attacks deteriorates
Solution Approach 1:
The patent combines multiple authentication modalities including facial recognition, depth sensing, and liveness detection into a unified authentication system. This multi-layered approach maintains user convenience while significantly improving security by requiring multiple conditions to be satisfied simultaneously for authentication to succeed.
Solution Approach 2:
The system performs preliminary liveness detection and depth analysis before completing authentication. By checking for signs of spoofing attempts in advance, the system prevents fraudulent authentication while maintaining a smooth user experience for legitimate users.
2Productivity
If picture frames-based facial recognition is used, then authentication speed is improved, but vulnerability to deepfake attacks increases
Solution Approach 1:
The patent introduces depth sensing and liveness detection as intermediary verification layers between the facial recognition process and final authentication. These intermediary checks analyze physical characteristics and temporal patterns that are difficult to replicate in deepfakes, thereby maintaining speed while improving security.
Solution Approach 2:
The system uses temporal analysis and liveness detection that require the subject to perform dynamic actions or respond to changing stimuli. This dynamic verification process makes static deepfake images ineffective while maintaining rapid authentication for legitimate users.
3Device complexity
If single-factor authentication is used, then system complexity is reduced, but security against compromised credentials deteriorates
Solution Approach 1:
The patent merges multiple authentication factors including biometric data, behavioral patterns, and contextual information into a unified authentication framework. This combination provides robust security against compromised credentials while presenting a seamless user experience that masks the underlying complexity.
Solution Approach 2:
The authentication system is designed to universally accept multiple types of authentication data and verification methods through a single interface. This multi-functional approach enhances security by considering multiple factors simultaneously while maintaining simple user interaction.
Data Source
AI summary
The present invention discloses a motion vision-based multimodal authentication system and a method thereof. The system comprises several components, including an information-capturing module, an AI module, a memory unit, a processor unit, and a temporal authentication module. The system captures information data from the user and the user's surroundings, categorize the data into identity and predetermined categories, generates login credentials or authorization keys, and matches the real-time information data for user authorization.