Eye Movement Authentication via Dynamic Grid Display
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Solution Overview
Problem
Current authentication methods lack robustness and security, as they rely on static biometric criteria that can be compromised or replicated, especially in scenarios where the user's state changes, such as fatigue or stress.
Innovation Solution
An eye movement-based authentication system that records and analyzes patterns of eye movements to verify user knowledge of embedded information, such as passwords, using a grid or matrix display where characters are dynamically rearranged, ensuring unique and changing patterns that are difficult to replicate.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If static biometric criteria are used for authentication, then the authentication process is simple, but the security and robustness are compromised
Solution Approach 1:
The patent transitions from static biometric criteria to dynamic eye movement patterns. The system captures and analyzes sequences of eye movements (saccades and fixations) as the user searches for information, creating a dynamic authentication mechanism that adapts to natural user behavior rather than relying on fixed biometric data.
Solution Approach 2:
The system changes the authentication parameter from static biometric properties to dynamic eye movement characteristics. By measuring parameters such as saccade amplitude, fixation duration, and search patterns, the system creates a more robust authentication mechanism that reflects actual user cognitive processes.
2Reliability
If eye movement patterns are used for authentication, then the security and robustness are enhanced, but the device complexity increases
Solution Approach 1:
The system uses a display device that serves multiple functions: presenting information to the user and simultaneously capturing eye movement data for authentication. This multi-functionality reduces the need for separate dedicated authentication hardware, thereby limiting the increase in device complexity.
Solution Approach 2:
The authentication process leverages the user's natural information-seeking behavior without requiring additional user actions. The system passively captures eye movement patterns as the user naturally searches for information on the display, eliminating the need for separate authentication interactions or specialized user training.
3Reliability
If dynamic character rearrangement is used, then the authentication robustness is improved, but the processing time increases
Solution Approach 1:
The system pre-processes and stores eye movement pattern templates during user registration or initial authentication. These templates capture the user's characteristic eye movement patterns when searching for information. During subsequent authentication attempts, the system compares new eye movement data against these pre-established templates, significantly reducing real-time processing requirements.
Solution Approach 2:
The system analyzes only the most distinctive and reliable features of eye movement patterns (such as saccade sequences and fixation patterns) rather than processing every detail of the eye movement data. This selective analysis maintains authentication robustness while minimizing processing time.
Data Source
AI summary
Embodiments of methods, apparatuses, and storage mediums associated with eye movement based knowledge demonstration, having a particular application to authentication, are disclosed. In embodiments, a computing device may determine whether a received input of a pattern of eye movements is consistent with an expected pattern of eye movements of a user when the user attempts to visually locate a piece of information embedded in a display. In embodiments, the expected pattern of eye movements may include patterns related to fixations and/or other statistical patterns, however, may not be limited to such patterns. In applications, determining consistency or correlation with the expected pattern of eye movements may identify the user by simultaneously verifying at least factors of authentication—that of biometric criteria related to a user's pattern of eye movements and a password or other information known to the user.