Device Metadata Comparison for Authentication Risk
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Solution Overview
Problem
Conventional authentication systems face challenges in accurately determining device risk levels for client devices, leading to false positives and lag times in denying access to malicious devices, as they rely on disjoint processes and information that can be spoofed or not provided.
Innovation Solution
An authentication system compares device metadata for impersonating client devices to enrolled devices to detect anomalies, using authentication credentials and metadata to determine a risk level, thereby authorizing or denying access requests based on the likelihood of the device being malicious.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional authentication systems use isolated snapshots of device information and complex analysis to determine risk levels, then they can identify potential malicious devices, but they produce false positives and require laggy disjoint processes
Solution Approach 1:
The patent merges the authentication process and risk level determination process into a single integrated flow. The risk level is determined concurrently with authentication by comparing device metadata from the current request against stored metadata from the enrolled device, eliminating the need for separate disjoint processes and reducing lag time.
Solution Approach 2:
The system performs preliminary actions by storing device metadata during the enrollment phase before authentication occurs. This pre-captured metadata is then readily available for immediate comparison during authentication, eliminating the need for complex real-time analysis and reducing processing time.
2Ease of operation
If conventional systems rely on information that can be spoofed or not provided, then they can simplify authentication, but they reduce security effectiveness
Solution Approach 1:
The system captures and stores a copy of the original device metadata during enrollment, including hardware identifiers and software characteristics. This copied metadata serves as a reference fingerprint that can be compared against future authentication requests, providing reliable verification without requiring users to manually provide information that could be spoofed.
3Reliability
If authentication systems use complex analysis of device information, then they can improve risk detection, but they increase false positives
Solution Approach 1:
Instead of performing complex comprehensive analysis of all device information, the system uses a simplified approach by comparing specific key metadata fields such as device identifiers, hardware characteristics, and software versions. This partial action approach maintains effective risk detection while avoiding the false positives associated with over-complex analysis.
Data Source
AI summary
An authentication system determines a risk level for a client device impersonating a client device enrolled in authentication services by comparing device metadata for the impersonating client device to device metadata for the enrolled client device. As part of enrolling the enrolled client device, the authentication system associates one or more authentication credentials with the enrolled client device. In order to authenticate access requests associated with a client device identified as the enrolled client device, the authentication system obtains an authentication token from the client device generated using the authentication credentials and also obtains device metadata corresponding to the client device. Based on the device metadata comparison during authentication, the authentication system detects device metadata anomalies and uses detected device metadata anomalies to determine a risk level for the client device. Based on the risk level, the authentication system authorizes or denies the client device from accessing requested services.