Biometric Authentication Replay Attack Prevention
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Solution Overview
Problem
Biometric authentication systems face challenges in preventing replay attacks, where attackers use previously authenticated biometric data to gain unauthorized access, as existing methods struggle to detect slight deviations in biometric data effectively.
Innovation Solution
The method involves defining a reference region and a blackout region for biometric data, where a positive authentication is granted only if the received data is within the reference region but outside the blackout region, with the blackout region updated after each successful authentication to detect and prevent replay attacks. This approach uses probability thresholds to adapt to the specific application and dynamically calibrate the reference biometric data set, reducing data storage requirements by representing biometric data with p-parameters.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If biometric data is stored and compared against reference data to enable authentication, then authentication functionality is achieved, but replay attacks become possible where attackers use previously authenticated biometric data to gain unauthorized access
Solution Approach 1:
The system performs preliminary actions by storing not only the reference biometric data but also the actual biometric data from previous successful authentications in a blackout region. This preliminary storage enables the system to detect and prevent replay attacks by comparing current authentication attempts against both the reference data and previously authenticated data, thereby resolving the contradiction between enabling authentication and preventing replay attacks.
Solution Approach 2:
The system implements feedback mechanisms by continuously updating the blackout region with biometric data from successful authentications and using this feedback to evaluate subsequent authentication attempts. The evaluation function uses feedback from previous authentications to determine whether current attempts are legitimate or replay attacks, thus maintaining security while allowing legitimate access.
2Reliability
If the blackout region is expanded to detect more replay attacks, then security against replay attacks improves, but legitimate users may be incorrectly rejected
Solution Approach 1:
The system applies local quality by creating distinct regions with different properties: the reference region for legitimate authentication and the blackout region for replay detection. Each region has specific characteristics - the reference region contains the enrolled biometric data while the blackout region contains previously authenticated data. This local differentiation allows the system to distinguish between legitimate users and attackers, improving replay detection without incorrectly rejecting legitimate authentications.
Solution Approach 2:
The system uses parameter changes by dynamically adjusting the blackout region based on the time window and probability thresholds. The evaluation function changes parameters such as the time window for considering previous authentications and the probability threshold for determining replay attacks. This dynamic parameter adjustment allows the system to adapt to different security requirements while maintaining ease of operation for legitimate users.
3Reliability
If biometric data and authentication history are stored to enable replay detection, then security improves, but data storage requirements increase
Solution Approach 1:
The system extracts only the necessary information for replay detection by storing biometric data in a compressed or processed form within the blackout region. Instead of storing complete biometric templates indefinitely, the system extracts and stores only the essential characteristics from previous successful authentications within a defined time window. This extraction approach reduces data storage requirements while maintaining effective replay attack prevention.
Solution Approach 2:
The system implements discarding and recovering by managing the blackout region with a time window that automatically discards old authentication data beyond the window limit. This discarding mechanism prevents unlimited data accumulation while the recovering aspect ensures that recent authentications within the time window are retained for replay detection. This approach balances security requirements with data storage constraints.
Data Source
AI summary
A method for authentication by biometric data, including receiving a biometric data set; evaluating if the received biometric data set is within a reference region, wherein the reference region represents a region associated with a reference biometric data set; evaluating if the received biometric data set is within a blackout region, wherein the blackout region represents a region associated with at least one previously received and positively authenticated biometric data set; and issuing a positive authentication if the received biometric data set is within the reference region, but outside the blackout region.