Authentication Bypass Detection Platform
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Solution Overview
Problem
Existing online authentication systems face challenges in detecting successful bypasses, which can lead to security breaches, as traditional methods rely on user reporting and fail to identify 'silent' bypasses, and do not effectively differentiate between malicious and non-malicious user activities.
Innovation Solution
An authentication bypass detection (ABD) platform that analyzes webpage logs and authentication logs to identify users who have bypassed the authentication system by correlating web traffic with authentication factor entries, determining the number of required and provided authentication factors, and generating a score based on web browsing behavior categories.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional authentication systems are used, then user identity verification is provided, but successful bypasses cannot be detected
Solution Approach 1:
The system implements feedback by continuously monitoring webpage logs and authentication logs, comparing actual authentication factor provision against expected requirements, and generating alerts when bypasses are detected. This closed-loop feedback mechanism enables the system to self-diagnose security breaches without user reporting.
Solution Approach 2:
The patent introduces an intermediary detection system that sits between the authentication system and users, analyzing log data to identify bypasses. This intermediary layer processes webpage logs and authentication logs independently, comparing them to detect discrepancies indicating bypass attempts without interfering with normal authentication operations.
2Productivity
If user reporting methods are used for bypass detection, then some bypasses can be identified, but 'silent' bypasses remain undetected and response time is delayed
Solution Approach 1:
The system performs preliminary action by proactively analyzing authentication logs and webpage logs in real-time to detect bypasses before users can report them. The system continuously compares expected authentication requirements with actual authentication events, identifying bypasses immediately upon occurrence rather than waiting for user discovery and reporting.
Solution Approach 2:
The detection system operates autonomously using self-service principles, automatically collecting log data, analyzing patterns, comparing authentication factors against requirements, and generating bypass detection results without human intervention. This self-serve mechanism eliminates dependency on user reporting and enables continuous automated surveillance of authentication security.
3Measurement precision
If authentication logs and webpage logs are analyzed, then bypass detection accuracy is improved, but system complexity increases
Solution Approach 1:
The system applies segmentation by dividing the log analysis process into distinct modules: one module collects and processes authentication logs, another processes webpage logs, and a third compares the two data streams to detect bypasses. This segmentation allows each module to specialize in specific tasks, improving detection accuracy while managing complexity through modular design.
Solution Approach 2:
The detection system implements multi-functionality by using a unified analysis framework that processes both authentication logs and webpage logs through the same comparison engine. This universal approach enables the system to handle multiple log types and detection scenarios with a single integrated system rather than requiring separate specialized systems for each log type.
Data Source
AI summary
Implementations are directed to detecting bypass of an authentication system of a web application with actions including receiving one or more webpage logs including web traffic associated with a web application during a defined time period, receiving one or more authentication logs associated with one or more authentication appliances providing authentication services for the web application, determining, based on the one or more webpage logs, one or more webpage log entries corresponding to a user and the defined time period, determining, based on the one or more authentication logs, a total number of correct authentication factors provided by the user during the defined time period, and determining, based on the one or more webpage log entries corresponding to the user and the defined time period and the total number of correct authentication factors provided by the user, that the user bypassed an authentication system of the web application.