Transaction Authentication Using User State Confidence Checks
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Solution Overview
Problem
Current payment transaction systems lack sufficient security measures to prevent fraudulent transactions, especially in scenarios where the user's location or condition is incompatible with initiating the transaction.
Innovation Solution
A method and system that utilize user state information from devices associated with the user, such as smart devices and network connections, to determine a user's location and condition, and require additional authentication if the confidence criterion is not met, enhancing security by cross-checking the legitimacy of the transaction.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If standard device and environment checks are performed to verify account holder identity, then transaction security is improved, but the system remains vulnerable to sophisticated fraud mechanisms
Solution Approach 1:
The system performs preliminary checks on user state information (location, device condition, network environment) before processing the transaction request. This advance verification ensures that the user is in a legitimate state to initiate the transaction, preventing fraud before it occurs by rejecting requests that don't meet predefined confidence criteria
Solution Approach 2:
The system continuously monitors and collects user state information from multiple sources (GPS location, device sensors, network data) and uses this feedback to dynamically assess transaction legitimacy. The confidence criterion evaluation provides feedback on whether to proceed with or reject the transaction, creating a closed-loop security system that adapts to detected anomalies
2Reliability
If additional authentication information is requested from users, then transaction legitimacy verification is improved, but user convenience and transaction speed deteriorate
Solution Approach 1:
The system automatically collects and evaluates user state information (location data, device status, network environment) without requiring active user participation. The confidence criterion assessment and authentication decisions are performed automatically by the system, eliminating the need for users to manually provide additional verification information in most cases
Solution Approach 2:
The system dynamically adjusts the confidence criterion threshold and authentication requirements based on the assessed risk level and user state. When user state information indicates low risk (high confidence), no additional authentication is required. When anomalies are detected (low confidence), the system selectively requests specific authentication information, optimizing the balance between security and convenience
3Measurement precision
If user state information is collected from multiple devices to determine user location and condition, then fraud detection capability is improved, but system complexity increases
Solution Approach 1:
The system uses a unified confidence criterion evaluation mechanism that processes multiple types of user state information (location, device condition, network data) through a single assessment framework. This multi-functional approach allows the same system components to handle diverse data sources without requiring separate processing pipelines for each type of information
Solution Approach 2:
The system introduces an intermediary confidence criterion evaluation layer that mediates between the diverse user state information sources and the final transaction decision. This intermediary component standardizes and integrates data from multiple devices and sources, transforming heterogeneous information into a unified confidence score that drives authentication decisions without requiring complex direct integration between all data sources
Data Source
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AI summary
A method for processing a transaction interaction between a first device and a payment processing device. The method is implemented by a remote server and comprises receiving a transaction request associated with a payment account of a user and generated during the transaction interaction, and receiving user state information from at least one second device associated with the user. The method further comprises determining a state of the user based on the user state information, and determining whether the state of the user satisfies a confidence criterion. In dependence on the state of the user failing to satisfy the confidence criterion, the method then requests authentication information from the user in order to determine whether to approve the transaction request.