Context-Aware Biometric Authentication Engine
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Solution Overview
Problem
As online transactions increase, existing security and authentication methods, such as passwords, become insufficient against sophisticated malicious actors, necessitating more secure authentication solutions.
Innovation Solution
The use of an apparatus and method that employs multiple biometric sensors to measure various biometric attributes, such as fingerprints, facial recognition, and gait, to enhance authentication security, combined with artificial intelligence/machine learning for contextual analysis to determine the appropriate biometric sensors for authentication.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If multiple biometric sensors are used to measure different biometric attributes, then authentication security is improved, but device complexity increases
Solution Approach 1:
The patent combines multiple biometric sensors (fingerprint sensor, facial recognition camera, gait analysis camera) into a single authentication device, merging their functions to provide multi-factor biometric authentication. This consolidation improves security while managing device complexity by integrating rather than separately deploying multiple sensing systems.
Solution Approach 2:
The authentication device is designed with multi-functionality, capable of performing multiple types of biometric authentication (fingerprint, facial recognition, gait analysis) through a single device. This universal approach allows the system to adapt different authentication methods based on context, improving security without requiring separate dedicated devices for each biometric modality.
2Adaptability or versatility
If contextual analysis using AI/ML is implemented to determine appropriate biometric sensors, then authentication adaptability is improved, but computational requirements increase
Solution Approach 1:
The system performs preliminary contextual analysis using AI/ML algorithms to determine which biometric authentication method is most appropriate before initiating the actual authentication process. By pre-assessing the context (transaction type, user behavior, security requirements), the system can select the most suitable biometric sensor, improving adaptability while managing computational load by avoiding unnecessary authentication methods.
Solution Approach 2:
The authentication system dynamically adapts its behavior based on contextual factors, adjusting which biometric sensors are activated and how they are used. The AI/ML component enables real-time decision-making about authentication requirements, allowing the system to be more demanding when security risks are higher and more lenient when risks are lower, thereby improving adaptability while optimizing resource usage.
Data Source
AI summary
Apparatus and methods content-based biometric authentication are provided. The apparatus and methods may include multiple biometric sensors and an authentication engine that decides which sensor(s) to use through a context-based analysis. The apparatus and methods may include requesting authentication, analyzing the request to determine which sensor(s) is appropriate, prompting a user to use the sensor(s) and comparing the data received with data stored in a database to provide authentication.