Mobile Payment Verification Using Weighted Location Data
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Solution Overview
Problem
Electronic transaction systems are vulnerable to attacks that redirect payments to unauthorized parties, particularly through false QR codes and skimming methods, compromising transaction security.
Innovation Solution
A transaction security system that uses weighted location data to verify transactions by comparing current transactions with historical data from the same location, alerting users to potential fraud and allowing confirmation from the vendor or point of purchase.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If QR code payment systems are used for touchless transactions, then transaction convenience and speed are improved, but vulnerability to false QR codes and payment redirection attacks increases
Solution Approach 1:
The system performs preliminary verification by analyzing historical transaction data and location information before processing the payment. It checks whether the QR code and transaction details match expected patterns from the merchant's location and history, preventing fraud before the transaction completes
Solution Approach 2:
The system uses historical transaction data as feedback to verify current transactions. By comparing current QR code transactions against historical patterns at the same location, the system can identify and block anomalous transactions that deviate from established merchant behavior
2Reliability
If location data verification is implemented to detect falsified payee information, then transaction security is improved, but system complexity increases
Solution Approach 1:
The system introduces location data and historical transaction patterns as intermediary verification layers between the user and the payment processing. These intermediaries provide additional security without requiring direct changes to the core payment infrastructure
Solution Approach 2:
The system creates a virtual model of legitimate merchant transactions by copying and analyzing historical transaction data. This digital twin of normal transaction patterns serves as a reference for verifying current transactions, adding security through data replication rather than hardware complexity
Data Source
AI summary
The system and methods describe transaction spoofing detection based on a transaction notification from a mobile computing device, determining a location associated with the mobile computing device, determining an entity associated with the location that the transaction notifications are directed to at the geographic location, determining whether the transaction is directed to the first entity and providing an indication on the first mobile computing device indicating the transaction may be a security risk.


