Eye Movement Tracking for Passive Affective Authentication
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Solution Overview
Problem
Traditional biometric authentication methods rely on physical characteristics, which can be spoofed and do not account for a person's inner identity, memories, likes, and dislikes, making them less secure and user-friendly.
Innovation Solution
The implementation of a passive affective and knowledge-based authentication (AKBA) system that captures eye movement and ocular dynamics data while a user interacts with a graphical user interface, generating a unique AKBA signature for authentication.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional biometric authentication methods are used, then physical characteristics can be captured for identification, but the authentication can be spoofed and does not reflect a person's inner identity
Solution Approach 1:
The patent combines multiple authentication modalities including iris recognition, face recognition, and knowledge-based questions into a unified biometric authentication system. This merging of physical characteristic recognition with cognitive assessment creates a more reliable authentication method that is harder to spoof while maintaining manageable system complexity through integrated processing
2Reliability
If physical characteristic-based biometric methods are used, then identification can be performed, but the method does not account for a person's inner identity, memories, likes, and dislikes
Solution Approach 1:
The patent introduces knowledge-based questions about a person's inner identity, memories, and preferences as an intermediary layer between physical biometric capture and authentication verification. This mediator adds a cognitive dimension that reflects true identity without significantly complicating the user experience, as the questions are naturally integrated into the authentication flow
Data Source
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AI summary
Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for authenticating a user based on passive affective and knowledge-based authentication (AKBA). In one aspect, a method includes data associated with eye movements and ocular dynamics of the user are captured with a camera as the user looks at a graphical user interface (GUI) of a device; an AKBA signature of the user is determined based on the captured data; the user is authenticated based on a comparison of the AKBA signature with an AKBA template associated with the user; and an access to a subset of functions of an application is granted.