Facial Micro-Expression Sequence Authentication Against Snooping
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Solution Overview
Problem
Existing methods for user authentication, such as password protection and biometrics, are vulnerable to snooping and compromise, particularly in high-value targets, and lack robustness in virtualization-based cloud environments.
Innovation Solution
Implement facial micro-expression sequence analysis using a facial micro-expression mapping to authenticate users, where a sequence of facial micro-expressions is mapped to a series of facial micro-expression letters, and compared to a stored sequence for authentication, optionally combined with traditional password entry.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional password or biometric authentication is used, then user authentication can be implemented, but the system remains vulnerable to snooping and compromise
Solution Approach 1:
The patent introduces facial micro-expressions as an intermediary layer between the user and the authentication system. Instead of directly observing passwords or static biometrics, the system captures transient facial muscle movements that occur naturally during authentication attempts. This intermediary mechanism transforms the authentication process from direct observation to indirect measurement through physiological responses, making snooping significantly more difficult while maintaining reliability.
Solution Approach 2:
The system transitions from static authentication methods (passwords, fingerprints) to dynamic authentication based on facial micro-expressions. These micro-expressions are transient, involuntary physiological responses that change continuously during the authentication process. By capturing and analyzing these dynamic patterns rather than static states, the system achieves higher reliability while reducing vulnerability to snooping, as dynamic patterns are much harder to replicate or observe remotely.
2Ease of operation
If immutable biometrics are used for authentication, then user identification can be performed, but the system lacks flexibility and additional security layers
Solution Approach 1:
The patent merges traditional biometric authentication with behavioral analysis of facial micro-expressions. Instead of relying solely on immutable biometrics like fingerprints or facial structure, the system combines these with dynamic micro-expression patterns. This merging creates a multi-layered authentication approach that maintains the ease of operation of biometrics while adding the adaptability and security of behavioral analysis, allowing the system to flexibly respond to different security requirements.
Solution Approach 2:
The authentication system uses a composite approach combining multiple authentication factors: static biometric data (facial structure) and dynamic behavioral data (micro-expression sequences). This composite authentication mechanism provides both the convenience of single-factor biometric login and the versatility of multi-factor authentication, as the system can adjust the weight and requirement of each factor based on security needs while maintaining user-friendly operation.
Data Source
AI summary
Systems and methods for improved security by facial micro-expression sequence are described. In an illustrative, non-limiting embodiment, an Information Handling System (IHS) may include: a processor; and a memory coupled to the processor, where the memory includes program instructions store thereon that, upon execution by the processor, cause the IHS to: obtain a video or a series of images of at least a portion of a face of a user of the IHS; determine a sequence of micro-expressions from the video or series of images; compare the determined sequence of micro-expressions to a stored sequence of micro-expressions; and authenticate the user based, at least in part, on the comparison indicating a match.