Facial Micro-Movement Authentication for Attack-Resistant User Authentication
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Solution Overview
Problem
Existing biometric authentication mechanisms, such as facial recognition, are vulnerable to attacks and lack sufficient resistance, as they rely on immutable biometric features that can be easily mimicked.
Innovation Solution
Authentication is enhanced by recognizing facial micro-movements during a prompted facial gesture, utilizing user-specific reference samples to verify the authenticity of the user.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If facial recognition is used for authentication, then the authentication process is seamless and easy to use, but the security resistance against attacks is insufficient
Solution Approach 1:
The patent transitions from static facial recognition to dynamic facial micro-movement analysis. The system captures and analyzes real-time facial muscle movements (micro-expressions) that occur naturally during authentication, making the biometric data dynamic and difficult to replicate with static masks or casts.
Solution Approach 2:
The patent changes the authentication parameter from static facial geometry to dynamic facial muscle movement patterns. By measuring subtle changes in facial feature positions over time during a prompted gesture, the system obtains a new biometric parameter that is much harder to spoof while maintaining ease of use.
2Ease of operation
If biometric features are used for authentication, then the authentication is seamless, but the features are immutable and cannot be changed if compromised
Solution Approach 1:
The system uses dynamic facial movements rather than static biometric features. Since the authentication is based on movement patterns during a prompted gesture rather than immutable physical traits, the system gains adaptability - if compromised, the gesture prompt can be changed while maintaining the same authentication mechanism.
3Reliability
If facial micro-movements are used for authentication, then the resistance against attacks is improved, but the measurement and detection difficulty increases
Solution Approach 1:
The system prompts the user to perform a specific facial gesture before capturing the micro-movements. This preliminary action standardizes the authentication process and ensures that the facial muscles are actively engaged, making the micro-movements more detectable and consistent across different users.
Solution Approach 2:
The patent adds the time dimension to facial recognition by analyzing facial micro-movements over time. Instead of a single static image, the system captures a sequence of facial states during a gesture, transforming the problem from 2D spatial recognition to 3D spatio-temporal analysis, which improves detectability of subtle movements.
Data Source
Figure 1a~1b
Figure 1c~2
AI summary
Examples relate to a method, an apparatus and a computer program for authenticating a user. The method comprises prompting the user to perform a facial gesture. The method comprises recording a facial gesture performed by the user using a visual sensor. The method comprises comparing micro-movements of the user's facial features during the recorded facial gesture with a user-specific reference sample of micro-movements for a specific facial gesture. The method comprises authenticating the user based on a match between the micro-movements of the user's facial features during the recorded facial gesture and the user-specific reference sample of micro-movements for the specific facial gesture.