Device Fingerprint Assignment via Attribute Correlation
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Solution Overview
Problem
Current security measures for internet devices are inadequate in efficiently identifying and protecting against fraudulent activities, as existing methods lack effective means to associate device fingerprints with user behaviors to enhance security.
Innovation Solution
A method and apparatus for assigning device fingerprints to target devices by acquiring attributes such as browser plug-ins and fonts, calculating correlation values with stored device fingerprints, and assigning or creating new fingerprints based on pre-determined threshold values, allowing for efficient security measures to be employed.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If device fingerprints are assigned to internet devices for security purposes, then security protection against fraudulent activities is improved, but the complexity of the system increases due to the need for attribute acquisition, correlation calculation, and fingerprint management
Solution Approach 1:
The system performs preliminary actions by pre-acquiring device attributes (browser plug-ins, fonts, screen resolution, etc.) and pre-calculating device fingerprints before security verification is needed. These attributes are stored in a device library for quick comparison during authentication, eliminating the need for complex real-time analysis and reducing system complexity during actual security operations.
Solution Approach 2:
The patent introduces an intermediary mechanism - the device fingerprint itself - which serves as a mediator between the device's complex attributes and the security verification process. Instead of directly analyzing multiple device attributes during verification, the system uses the pre-computed fingerprint as an intermediary identifier, simplifying the security check while maintaining reliability.
2Measurement precision
If correlation values are calculated between device attributes and stored fingerprints to determine device identity, then measurement precision of device identification is improved, but the computational time and processing resources increase
Solution Approach 1:
The system applies partial action by selecting and comparing only key device attributes (such as browser plug-ins and fonts) rather than analyzing all possible device characteristics. This selective approach maintains sufficient identification accuracy while significantly reducing computational time and processing resources required for correlation calculation.
Solution Approach 2:
The patent transforms the complex multi-dimensional device attributes into a simplified fingerprint parameter representation. By changing the parameter form from multiple raw attributes to a condensed fingerprint identifier, the system enables faster correlation calculation while preserving the essential information needed for accurate device identification.
3Adaptability or versatility
If a device library storing multiple device fingerprints is maintained for comparison, then the versatility of device identification is improved, but the quantity of data stored and processing overhead increase
Solution Approach 1:
The system extracts only the essential identifying characteristics from device attributes to create compact fingerprints. By taking out only the most distinctive and relevant features (such as specific plug-in combinations, font sets, and screen configurations) and storing them as condensed fingerprints in the device library, the system maintains versatile device identification capability while minimizing data storage requirements.
Data Source
AI summary
A method for assigning a device fingerprint to a target device is provided. The method includes acquiring first attributes of the target device, the first attributes including at least one browser plug-in or one font; calculating a correlation value with respect the first attributes of the target device and second attributes of at least one second device having a device fingerprint stored in a device library. The first attributes correspond to the second attributes. The method further includes: if the correlation value is greater than or equal to a pre-determined threshold value, assigning the device fingerprint of the at least one second device to the target device; and if the correlation value is smaller than the pre-determined threshold value, storing the first attributes of the target device to the device library and assigning a new device fingerprint to the target device.