Biometric Identity Authentication With Spoofing and Liveness Checks
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Solution Overview
Problem
Existing digital authentication methods lack robust security measures to prevent spoofing and ensure liveness verification, particularly in the context of mobile devices, which are crucial for secure access to sensitive information.
Innovation Solution
A multi-layered authentication method involving spoofing detection, liveness detection, identity biometrics, and time verification, utilizing machine learning techniques and image/audio processing to authenticate user identity through selfie captures.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional authentication methods are used, then ease of operation is maintained, but security against spoofing attacks deteriorates
Solution Approach 1:
The authentication process is divided into distinct functional modules: spoofing detection module that analyzes captures for artificial indicators, liveness detection module that verifies biological signs, identity verification module that confirms user identity, and time verification module that checks temporal consistency. This segmentation allows each module to specialize in one aspect of security while maintaining overall system manageability and ease of operation.
Solution Approach 2:
The patent introduces an intermediary authentication system between the user and the protected resource. This intermediary performs multi-layered verification including spoofing detection, liveness detection, identity verification, and time checking, thereby enhancing security without requiring the end user to directly manage complex security protocols.
2Reliability
If spoofing detection is added to authentication, then security improves, but device complexity increases
Solution Approach 1:
The authentication system is designed as a universal platform that can be integrated into various devices and applications. The spoofing detection, liveness detection, identity verification, and time checking functionalities are packaged as a cohesive multi-functional system that can serve different security needs across mobile devices, computers, and other platforms, thereby reducing overall system complexity through standardization.
Solution Approach 2:
The patent implements a nested authentication architecture where spoofing detection is embedded within the broader authentication flow, which itself is nested within the device's security framework. Each detection layer (spoofing, liveness, identity, time) operates as a nested component that builds upon previous layers, creating a compact hierarchical structure that manages complexity through organized nesting.
3Measurement precision
If multiple detection criteria are implemented, then measurement precision improves, but loss of time increases
Solution Approach 1:
The system performs preliminary actions by pre-configuring detection criteria, thresholds, and verification rules before authentication occurs. Spoofing indicators, liveness parameters, identity matching rules, and time window constraints are all established in advance, allowing the actual authentication process to quickly compare captured data against pre-set criteria rather than creating and evaluating rules in real-time, thereby reducing authentication time while maintaining precision.
Solution Approach 2:
The patent implements optimized verification pathways that can skip certain detection steps when conditions permit. For example, if initial spoofing detection passes and basic liveness is confirmed, the system can rush through to identity verification without performing more stringent secondary checks, unless anomalies are detected. This selective skipping maintains measurement precision for critical checks while reducing overall authentication duration through intelligent path optimization.
Data Source
AI summary
Methods for authenticating an identity of a person. One such method includes: obtaining, from a capturing device, one or more captures including image and/or audio captures; detecting, based on spoofing-detection criteria, spoofing indicators in the captures and whether the spoofing indicators correspond to spoofing indicia; detecting, based on liveness-detection criteria, biometric-features in the captures and whether the biometric-features correspond to liveness indicia; detecting, based on identity-biometric criteria, biometric attributes in the captures and whether the biometric attributes correspond to a predefined human identity; extracting, based on time-related criteria, a time-reference hidden or codified in the captures and detecting whether the time-reference satisfies predefined time constraints; and authenticating the identity of the person depending on whether spoofing indicia have been detected, whether liveness indicia have been detected, whether biometric attributes have been detected corresponding to predefined human identity, and whether the time-reference satisfies predefined time constraints.