Biometric Access Control Using ML Scoring
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Solution Overview
Problem
Traditional access control methods, such as physical tickets, are vulnerable to duplication and resale, leading to unauthorized access and loss of control over who enters restricted areas, which can compromise security and safety.
Innovation Solution
A method using machine learning to calculate a predicted score for users based on their preferences and behavior, allocating eligibility flags to determine access permissions, and utilizing biometric data for validation to ensure only authorized individuals enter restricted areas.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If physical tickets are used for access control, then ease of operation is improved, but reliability deteriorates due to duplication and resale vulnerabilities
Solution Approach 1:
The patent replaces physical mechanical tickets with a digital system using biometric data (fingerprint, facial recognition) and electronic validation. This substitution eliminates the physical duplication vulnerability while maintaining ease of operation through contactless digital verification at access points.
Solution Approach 2:
The patent introduces a centralized validation system as an intermediary between the user and the restricted area. This system verifies biometric data against a database and controls access dynamically, preventing unauthorized duplication while maintaining smooth user experience through automated validation.
2Reliability
If digitized tickets are used for access control, then reliability is improved by reducing duplication, but device complexity increases
Solution Approach 1:
The patent extracts the complex validation logic from the access control points and centralizes it in a remote server. The access points only need to capture biometric data and communicate with the server, significantly reducing on-site device complexity while maintaining high reliability through centralized control.
Solution Approach 2:
The patent uses biometric template matching where simplified digital representations of biometric data are stored and compared. This copying approach allows reliable verification without requiring complex storage and processing of raw biometric data at each access point.
3Ease of operation
If traditional access control is used, then ease of operation is maintained, but loss of information occurs through unauthorized resale and loss of user data
Solution Approach 1:
The patent implements continuous feedback loops where user data is collected, analyzed for anomaly detection, and used to update access control decisions in real-time. This feedback mechanism prevents information loss by identifying and blocking unauthorized resale attempts while maintaining normal user operations.
Solution Approach 2:
The patent performs preliminary validation of user identities and intentions before granting access. By verifying biometric data and checking against blacklists in advance, the system prevents unauthorized access and information loss before they can occur, while maintaining ease of operation for legitimate users.
Data Source
AI summary
An allocation method of allocating or not allocating a flag to a user which can be in turn be used to enable access by that user to a restricted area includes calculating a predicted score for the user using a pre-determined machine learning methodology, storing the predicted score in a database, calculating an eligibility score for the user based on the predicted score and an event coefficient, and if the eligibility score meets or exceeds a pre-determined threshold score, allocating a positive flag to the user in the database, otherwise allocating a negative flag to the user in the database.