Micro Acceleration Biometric Authentication via Gait Pattern Filtering
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Solution Overview
Problem
Current biometric authentication methods, such as fingerprints and retina scans, are obtrusive and inconvenient, necessitating a less intrusive and more convenient biometric factor for multi-factor authentication.
Innovation Solution
The use of micro accelerations, measured by accelerometers, as a biometric identification factor, where the unique patterns of a user's movements, such as their gait, are filtered and stored to authenticate the user's identity, serving as an additional factor in multi-factor authentication processes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional biometric factors like fingerprints and retina scans are used, then authentication security is improved, but user convenience and ease of operation deteriorate due to obtrusive methodologies requiring active user participation
Solution Approach 1:
The system uses passive biometric data collection through accelerometers that automatically capture micro-movement patterns without requiring active user participation. The authentication process serves itself by continuously monitoring natural movements and comparing them against stored patterns, eliminating the need for users to deliberately perform authentication actions.
Solution Approach 2:
The patent replaces traditional mechanical biometric collection methods (fingerprint scanners, retina scanners requiring physical contact or direct eye exposure) with inertial measurement-based detection. Accelerometers capture subtle movement patterns mechanically, substituting intrusive optical or contact-based systems with passive motion sensing.
2Ease of operation
If passive biometric factors are used to improve user convenience, then ease of operation is improved, but measurement precision and reliability may deteriorate due to environmental noise and variability
Solution Approach 1:
The system performs preliminary data collection and pattern establishment during a enrollment phase, storing reference micro-movement patterns for later comparison. This preliminary action creates a baseline that accounts for individual variability, enabling more accurate subsequent authentication decisions by comparing new measurements against established patterns.
Solution Approach 2:
The system continuously monitors micro-movement patterns and compares them against stored reference patterns in real-time. This feedback mechanism allows the system to dynamically assess authentication status based on ongoing movement data, adjusting security responses based on the degree of pattern matching and environmental conditions.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach provides a secure, convenient, and less obtrusive form of authentication, as a user's gait cannot be easily replicated or hacked, enhancing the integrity of two-factor authentication systems without requiring active user participation.
Implementation Method 1
receive micro acceleration data collected by one or more accelerometers
Data Source
AI summary
Systems and methods for using micro accelerations as a biometric factor for multi-factor authentication, the method including receiving, filtering, and determining an identifying pattern from micro acceleration data representative of the user, storing the identifying pattern for later use in authenticating the identity of the user, and using the identifying pattern as one factor in a multi factor authentication.