Duress Detection in Biometric Payment Systems
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Solution Overview
Problem
Biometric-based payment authorization systems are vulnerable to duress, where criminals may threaten users to force them to make payments or authorize access, rather than stealing physical payment devices.
Innovation Solution
A payment application that detects whether a user at a Point-of-Sale (PoS) device is under duress by analyzing biometric input and physiological parameters, and takes supplemental actions such as declining the transaction, flagging it for review, or requesting two-factor authentication.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If biometric-based payment authorization is implemented, then payment security is improved by reducing theft risk of physical payment devices, but the system becomes vulnerable to duress attacks where criminals force users to authorize transactions
Solution Approach 1:
The system performs preliminary biometric authentication before allowing payment, establishing a baseline of user identity. This preliminary action creates a security layer that prevents unauthorized use of physical payment devices while enabling subsequent duress detection through analysis of user state changes during the transaction process
Solution Approach 2:
The system continuously monitors user biometric data and physiological parameters during the payment process, providing real-time feedback on user state. This feedback mechanism enables the system to detect signs of duress (such as elevated heart rate, sweating, or abnormal movement patterns) and respond by canceling the transaction or alerting authorities, thus resolving the vulnerability to duress attacks
2Reliability
If biometric data analysis is performed to detect duress, then transaction security is improved, but system complexity and processing time increase
Solution Approach 1:
The system uses multi-functional biometric sensors that serve both authentication purposes and duress detection purposes. The same sensors that capture fingerprint or facial data also monitor physiological parameters like heart rate, skin conductance, and micro-expressions, eliminating the need for separate dedicated duress detection hardware and reducing overall system complexity
Solution Approach 2:
The system introduces an intermediary processing layer that analyzes biometric data streams and separates authentication verification from duress detection functions. This intermediary module processes sensor data efficiently, applying machine learning models to detect duress signs without requiring complex hardware modifications, thus managing system complexity while maintaining high transaction security
Data Source
AI summary
Systems and methods are described for enabling payment or access validation based on the state of a user. A user may initiate a transaction at a point-of-sale device by providing a biometric input. The user's affective state is determined based on the user's biometric input. If the probability that the user is under duress is above a threshold, a supplemental action is taken (e.g., denying the transaction, flagging the transaction for review, etc.).