Proximate Wireless Network Detection for Fraudulent Skimmer Identification
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Solution Overview
Problem
Access devices, such as ATMs and point of sale systems, are vulnerable to fraudulent schemes involving physical skimmers that read credit card information and communicate with fraudsters using Bluetooth or Wi-Fi transmitters, making it difficult to detect unauthorized wireless networks.
Innovation Solution
Implementing a system that processes authorization request messages by identifying and comparing wireless networks proximate to the access device or communication device, initiating actions if significant differences are detected, to detect potential fraudulent activity.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If wireless network detection is implemented to detect fraudulent skimmers, then security detection capability is improved, but device complexity and processing overhead increase
Solution Approach 1:
The patent introduces a communication device (smartphone, tablet, or laptop) as an intermediary to perform wireless network detection and analysis. This external device captures images of the access device, identifies potential skimmers, and communicates findings to the processing entity. By offloading the complex image analysis and network detection functions to a user's personal device, the access device itself remains relatively simple while still achieving enhanced fraud detection capability.
Solution Approach 2:
The system implements a feedback loop where the processing entity receives network data from communication devices, compares it against stored baseline data, and uses the results to update its understanding of legitimate versus fraudulent configurations. This continuous feedback mechanism allows the system to adapt to new fraud patterns while maintaining relatively simple processing rules at each individual access device.
2Measurement precision
If network data comparison is performed for every authorization request, then fraud detection accuracy is improved, but processing time and transaction speed increase
Solution Approach 1:
The system performs network data comparison selectively rather than for every single authorization request. The processing entity compares network data when there are changes in the wireless network environment or when triggered by specific conditions. This partial action approach maintains high detection accuracy for suspicious activities while avoiding the time penalty of comparing every single transaction against all historical data.
Solution Approach 2:
The system performs preliminary network data collection and baseline establishment during legitimate transactions. By accumulating network data from multiple sources and establishing baseline configurations in advance, the system prepares reference information that can be quickly compared against future transactions. This preliminary action reduces the real-time processing burden during actual authorization requests.
3Adaptability or versatility
If multiple communication devices are used to collect network data, then detection coverage is improved, but data management and processing complexity increase
Solution Approach 1:
The system is designed to accept network data from multiple types of communication devices (smartphones, tablets, laptops) that all perform the same basic function of capturing images and identifying wireless networks. By creating a universal data collection approach that works across different device types using common protocols and formats, the system achieves broad detection coverage while maintaining relatively simple data management. The processing entity handles diverse input sources through a standardized interface, reducing the complexity of managing multi-device data collection.
Data Source
AI summary
A methodology for processing authorization request messages based on proximate wireless networks is disclosed. In particular, a computer may receive, from an access device or a communication device, an authorization request message in a transaction. The computer may then obtain network data based on a set of wireless networks that are proximate to the access device or the communication device interacting with the access device during the transaction. Next, the computer may determine a difference between the network data and previous network data, wherein the previous network data is based on one or more previous sets of wireless networks that were proximate to the access device or the communication device during one or more previous transactions. Responsive to determining that the difference exceeds threshold, the computer may initiate one or more actions associated with the transaction.