Mobile Travel Path Analysis for Location Spoofing Detection
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Solution Overview
Problem
Existing systems fail to effectively detect and prevent malicious attacks that spoof a mobile device's location, as they rely on third-party servers and GPS coordinates, and cannot identify anomalous patterns in communication packets that do not trigger alarms.
Innovation Solution
A system and method that analyze the travel path of a mobile device across multiple geographic areas by comparing actual travel time with minimum transition time, using existing telecom protocols to identify suspicious or fraudulent activity without requiring real-time location queries or third-party servers.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If third-party servers and GPS coordinates are used to detect location spoofing, then location accuracy can be improved, but device complexity and infrastructure requirements increase
Solution Approach 1:
The patent extracts the location verification function from external third-party servers and GPS systems, and implements it within the mobile device itself using the device's existing sensors (accelerometer, gyroscope, magnetometer) and telecom network data. This eliminates the need for complex external infrastructure while maintaining location detection capability.
Solution Approach 2:
The mobile device performs its own location verification by analyzing data from its internal sensors and comparing it with telecom network location data. The device autonomously determines whether location spoofing is occurring without requiring external verification servers, making the system self-sufficient.
2Measurement precision
If real-time location queries are performed to detect spoofing, then detection accuracy improves, but system response time and energy consumption increase
Solution Approach 1:
The system continuously monitors and pre-processes location data from both the device sensors and telecom network in the background, maintaining a baseline of normal location patterns. When a location update is received, the verification is performed immediately by comparing against pre-established patterns, enabling rapid detection without time-consuming real-time queries.
3Measurement precision
If GPS coordinates are continuously monitored to identify spoofing, then location tracking precision improves, but energy consumption increases
Solution Approach 1:
The patent leverages the mobile device's existing sensor suite (accelerometer, gyroscope, magnetometer) which are already active for other functions like navigation, gaming, and fitness tracking. By repurposing these sensors for location spoofing detection, the system achieves location monitoring without additional energy consumption from dedicated GPS tracking.
4Reliability
If classic alarm algorithms are used to detect malicious packets, then false alarm rate reduces, but detection capability for sophisticated attacks decreases
Solution Approach 1:
Instead of analyzing only the traditional dimensions of packet content and protocol compliance, the patent adds a new dimension of physical feasibility by incorporating sensor data (acceleration, orientation, magnetic field) and telecom network location data. This multi-dimensional analysis enables detection of sophisticated spoofing attacks that appear valid in traditional analysis but are physically impossible.
Data Source
AI summary
A method for identification of malicious activity based on analysis of a travel path of a mobile device through multiple geographic areas includes receiving at least three location data associated with the mobile communication device, the first location data comprising indication of the geographic area of the mobile subscriber and a receipt timestamp; determining the actual travel time of the mobile subscriber from the first geographic area and the third geographic area based on a difference between timestamps of the first location data and the third location data; determining a minimum transition time for the subscriber of the mobile device to move from the first geographic area to the third geographic area; and identifying a malicious activity based on comparison of the actual travel time and the minimum transition time wherein actual travel time is less than minimum transition time between the first geographic area and the third geographic area.