Card And Wearable Geolocation Authentication With Dynamic AI Rules
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Solution Overview
Problem
Existing resource exchange event authentication systems rely on predefined location rules from mobile communication devices, which may not account for dynamic circumstances and are not applicable when such devices are unavailable, and lack flexibility in adapting to user-specific conditions.
Innovation Solution
A system using short-range wireless signals from cards or wearable devices, equipped with RFID, Zigbee, or Bluetooth Low Energy components, determines user location and applies AI/ML to dynamically set authentication rules based on current circumstances, including user location, time, and resource exchange details.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If location determination is based on mobile communication devices with GPS, then location accuracy is improved, but device complexity and cost increase, and accessibility decreases for users without such devices
Solution Approach 1:
The patent introduces an intermediary location determination system that uses fixed wireless infrastructure (cell towers, Wi-Fi access points) instead of requiring sophisticated mobile devices. The system acts as a mediator between the user and the location verification process, providing location services through network-based methods rather than device-based GPS technology.
Solution Approach 2:
The patent employs simpler, more affordable location determination technologies such as cell tower triangulation and Wi-Fi positioning, which are less expensive and more accessible than GPS-based systems. These methods use existing network infrastructure that is already deployed widely, providing cost-effective location services without requiring expensive specialized hardware.
2Device complexity
If predefined authentication rules are used, then system simplicity is maintained, but adaptability to dynamic circumstances deteriorates
Solution Approach 1:
The patent implements dynamic authentication rules that can change based on real-time conditions such as user location, time of day, transaction amount, and risk assessment. The system transitions from static predefined rules to dynamic rules that adapt to current circumstances, allowing authentication parameters to be adjusted automatically based on the specific situation while maintaining overall system simplicity through automated decision-making.
Solution Approach 2:
The patent changes authentication parameters dynamically based on detected conditions. For example, authentication requirements may change based on geographic location (stricter rules in high-risk areas), time of day, transaction value, or device trust level. This allows the system to maintain simplicity through automated parameter adjustment rather than requiring complex manual rule configuration for every scenario.
3Reliability
If location-based authentication rules are implemented, then authentication security is improved, but ease of operation deteriorates for users without mobile devices
Solution Approach 1:
The patent creates a universal authentication system that works across multiple device types and scenarios. Instead of requiring mobile devices with specific capabilities, the system provides location-based authentication through any device with a camera or through network-based location determination. This multi-functional approach ensures that users without sophisticated mobile devices can still benefit from secure location-based authentication.
Solution Approach 2:
The patent implements self-service authentication where the system automatically determines location and applies appropriate authentication rules without requiring user intervention. The system performs location detection, risk assessment, and authentication decision-making automatically, reducing the burden on users while maintaining high security standards.
Data Source
AI summary
Resource exchange event authentication predicated on user location that is determined from short-range wireless signals transmitted from a card or wearable device in possession of the user. Artificial Intelligence (AI), including Machine Learning (ML) techniques are relied on to determine an authentication rule and/or parameters for an authentication rule as part of the authentication process. Thus, at least a portion of the authentication rules and/or parameters, which may be based not only on the aforementioned determined location of the user, but also on other factors such as time, amount of resource exchange event, type of objects/services being exchanged in the event and the like, are determined intelligently and dynamically at the time that the resource exchange event occurs.