Location Matching for Multi-Device Unauthorized Access Detection
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Solution Overview
Problem
Malicious actors can gain unauthorized access to online systems by using multiple client devices simultaneously, compromising the security of location-based services.
Innovation Solution
An online system identifies matching client devices by comparing location data points collected by those devices, associating user profiles based on matching location data points within a threshold distance or geographic region, and applying a set of matching criteria to determine if multiple devices are operated by the same person.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the online system collects and compares location data points from multiple client devices, then the security against unauthorized access is improved, but the device complexity and data processing requirements increase
Solution Approach 1:
The system segments location data into discrete data points with timestamps and geographic coordinates, allowing individual processing and comparison. Each data point is independently validated against matching criteria, enabling scalable security checks without overwhelming system complexity.
Solution Approach 2:
The system introduces an intermediary comparison mechanism that evaluates location data points from different devices against predefined matching criteria. This intermediary layer automatically determines device relationships without requiring complex manual analysis, simplifying the overall system architecture.
2Measurement precision
If the online system applies matching criteria to location data points, then the accuracy of user identification is improved, but the processing time and computational resources increase
Solution Approach 1:
The system performs preliminary actions by pre-establishing matching criteria and thresholds for location data comparison. These criteria are defined in advance, allowing rapid automated evaluation of new location data points without time-consuming analysis during critical authentication moments.
Solution Approach 2:
The system applies partial matching criteria that focus on the most indicative features (geographic proximity, temporal coincidence, spatial relationship) rather than analyzing every possible data attribute. This selective approach maintains high identification accuracy while significantly reducing processing time.
3Reliability
If the system identifies matching client devices, then the prevention of unauthorized access is improved, but the ease of operation for legitimate users may be affected
Solution Approach 1:
The system performs self-service by automatically detecting and evaluating location data patterns without requiring user intervention. Legitimate users experience no additional steps, while the system autonomously identifies matching devices and applies security measures, maintaining ease of operation for authorized users.
Solution Approach 2:
The system implements feedback mechanisms that provide real-time information about device matching decisions to users when necessary. This feedback loop allows users to understand security actions taken against their devices while maintaining smooth operation, and enables adjustment of matching criteria based on user behavior patterns.
Data Source
AI summary
An online security system identifies matching client devices by comparing location data points acquired during application workflow from different devices. The location data points comprise a location of the device and a timestamp. Identifiable pairs of data points are collated from different devices when they show a device present within a threshold distance or the same geographic region at identical times. The system utilizes a set of matching criteria to decide whether one data set for one device corresponds with a set from another. Verification of the matches allows the system to ascertain the same user is operating both devices and link the user to both devices. This system enhances security by identifying users likely gaining unauthorized access through multiple device usage simultaneously.