Geolocation Accuracy via Network Time-of-Flight
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Solution Overview
Problem
Existing IP geolocation methods are prone to errors due to static databases and violate user privacy by providing precise location data, while self-reported GPS coordinates can be easily manipulated, lacking sufficient security and accuracy for fraud detection.
Innovation Solution
The N-4Tk method uses a geographically dispersed network of servers to calculate the time it takes for data to travel between a user's device and multiple servers, adjusting for bandwidth fluctuations and accounting for local delays, to determine a user's general location without pinpointing their specific location, enhancing security and privacy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If IP geolocation uses static databases with manual updates, then database maintenance is simplified, but geolocation accuracy deteriorates due to errors and delays in updating
Solution Approach 1:
The system performs self-updating by automatically discovering current IP-to-location mappings through active probing and measurement, eliminating the need for manual database updates while maintaining high accuracy through continuous self-correction
Solution Approach 2:
The system implements feedback loops where geolocation measurements are continuously performed and used to update the underlying database automatically, creating a self-correcting system that improves accuracy over time without manual intervention
2Reliability
If IP geolocation provides precise location data, then fraud detection capability is improved, but user privacy deteriorates due to needless violation of privacy and increased liability
Solution Approach 1:
The system extracts only the essential geolocation information needed for fraud detection (general location patterns) while deliberately excluding personally identifiable information, separating the useful security function from the harmful privacy violation
Solution Approach 2:
The system applies different levels of precision to different users based on their risk profiles, using higher precision only when necessary for fraud detection while maintaining lower precision for normal users to protect their privacy
3Loss of information
If GPS coordinates are used for location determination, then location data availability is improved, but security deteriorates because GPS coordinates can be easily manipulated by attackers
Solution Approach 1:
The system introduces an intermediary verification layer that measures actual network travel times between the user and multiple geographically distributed servers, creating a trusted mediation mechanism that prevents direct manipulation of location data while maintaining availability
Solution Approach 2:
The system combines multiple independent measurements (network travel times to multiple servers) into a single geolocation determination, creating a redundant system where a single manipulated measurement cannot compromise the overall security and accuracy
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach provides a secure and privacy-enhanced method for determining user location, making it harder for attackers to misrepresent their location and reducing unnecessary precision, while allowing for accurate proximity calculations without direct electronic communication between entities.
Implementation Method 1
the coordinates for any given location on the Internet is a measure of the time it takes for data to travel between the location and the N servers
Data Source
AI summary
The present innovation extends the innovations inherent in our prior work on security and privacy enhanced geolocation to address specific problems of determining the proximity of two Internet connected devices. This could be used for applications such as determining proximity of a user's smartphone to an ATM machine they are using. Or to determine the physical proximity of a shopper and a cashier at a check out line. A straightforward application of the prior work will not suffice, as devices may have very different types of connectivity to the Internet. We solve this problem by placing reciprocal slave servers on each of the devices and giving high weight to the time taken for messages to travel from each device to the slave on the other device. The system can be extended to more than two entities by performing the calculation in a pairwise fashion and using further optimizations.