Device Attribute Veracity via Processing Cycle Benchmarking
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Solution Overview
Problem
Existing systems face challenges in accurately detecting device attributes and identifying the presence of addons or extensions on computer devices, which can spoof fake attributes, leading to unauthorized transactions and security vulnerabilities.
Innovation Solution
A risk analysis system that estimates the number of processing cycles used by a computer device to perform specific functions, comparing the results to benchmark profiles to determine the veracity of device attributes and detect potential addons or extensions, thereby ensuring accurate authentication and transaction authorization.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If device fingerprints are used to track devices for suspicious transactions, then security against unauthorized transactions is improved, but malicious users can spoof fake device data using addons or extensions, making detection difficult
Solution Approach 1:
The system performs preliminary detection of device attributes and benchmarks processing cycle times before transactions occur. By establishing baseline performance metrics in advance, the system can later compare actual transaction device behavior against these pre-established benchmarks to identify spoofed devices, resolving the contradiction between maintaining security and detecting sophisticated spoofing attempts.
Solution Approach 2:
The system implements feedback mechanisms by continuously monitoring device processing cycle times and comparing them against benchmark profiles. When deviations are detected, the system provides feedback to flag potential spoofing attempts, enabling dynamic adjustment of security measures while maintaining the ability to detect sophisticated addons or extensions that attempt to mimic genuine device fingerprints.
2Ease of operation
If device attributes are obtained from computer devices for authentication, then authentication capability is improved, but the veracity of attributes cannot be verified, leading to potential fraud
Solution Approach 1:
The system replaces reliance on self-reported device attributes with a physics-based measurement approach. By measuring processing cycle times through benchmarking tasks and comparing them against established profiles, the system substitutes direct attribute reporting with indirect physical measurements that are harder to spoof, thereby improving both authentication capability and the veracity verification of device attributes.
Solution Approach 2:
The system changes the parameter being measured from static device attributes (which can be easily spoofed) to dynamic processing cycle times. By benchmarking how long a device takes to execute specific computational tasks and comparing these temporal parameters against known profiles, the system achieves more precise verification of device attribute veracity while maintaining ease of authentication operations.
Data Source
AI summary
Methods and systems are presented for assessing a veracity of device attributes obtained from a computer device based on estimating a number of processing cycles used by the computer device to perform a particular function. In response to receiving a transaction request from the computer device, software programming instructions are transmitted to the computer device for obtaining device attributes of the computer device. The software programming instructions may also include code that estimate a number of processing cycles used by the computer to perform a particular function. The particular function may be associated with obtaining at least one of the device attributes of the computer device. The estimated number of processing cycles may be compared against a benchmark profile. A risk associated with the transaction request is determined based on the comparing.