Passive forged browser detection via HTTP header analysis
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Solution Overview
Problem
Existing web servers are vulnerable to forged web browsers due to their inability to differentiate between real and malicious browsers based on User-Agent strings, leading to potential exploitation through velocity attacks.
Innovation Solution
A passive detection method that monitors web traffic between a web server and a client, processes HTTP request headers, and generates attribute data points based on browser behavior to compare with predetermined data points for genuine browsers, thereby identifying genuine or forged browsers without active page modification.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If the web service relies on User-Agent string identification to differentiate browsers, then the detection method is simple, but the web service cannot differentiate between real and forged browsers, leaving it vulnerable to exploitation
Solution Approach 1:
The patent segments the browser identification process into multiple independent attribute analyses (HTTP header fields, connection behavior, request patterns) rather than relying on a single User-Agent string check. Each attribute is evaluated separately and combined to form a comprehensive browser fingerprint, enabling accurate differentiation between genuine and forged browsers while maintaining manageable system complexity
Solution Approach 2:
The patent introduces an intermediary detection layer that analyzes multiple attributes (HTTP headers, connection behavior, request patterns) between the client and web service. This intermediary analysis layer acts as a mediator that verifies browser authenticity without requiring modification to the core web service, resolving the contradiction by adding verification capability without proportionally increasing overall system complexity
2Measurement precision
If active page modification is used to detect forged browsers, then detection accuracy improves, but processor and network load increase significantly
Solution Approach 1:
The patent performs preliminary analysis of browser attributes (HTTP header fields, connection behavior, request patterns) during the initial connection phase before any page modification or active testing occurs. By pre-establishing a browser fingerprint from passive observation, the system achieves accurate detection without the energy cost of active page modification, as the detection data is collected during normal browsing operations
Solution Approach 2:
The patent enables the browser to essentially identify itself through its own behavior patterns and attribute characteristics. Genuine browsers naturally exhibit consistent, expected behaviors in HTTP headers, connection management, and request patterns, while forged browsers fail to replicate these patterns. This self-identification approach eliminates the need for external active testing, significantly reducing processor and network load while maintaining high detection accuracy
3Measurement precision
If comprehensive attribute analysis is performed to identify forged browsers, then detection accuracy improves, but the system complexity increases
Solution Approach 1:
The patent creates a universal detection framework that uses the same multi-attribute analysis approach for all browser types and scenarios. The system evaluates HTTP header fields, connection behavior, and request patterns using consistent criteria regardless of the specific browser or attack variant, making the detection system highly accurate while managing complexity through standardization and reusability of the analysis methodology
Solution Approach 2:
The patent implements feedback mechanisms where detection results from attribute analysis are continuously refined and used to improve future detection accuracy. The system learns from observed browser behaviors and adjusts its attribute evaluation criteria, enabling high detection accuracy while the feedback loop automates much of the complexity management, reducing the need for manual system configuration and maintenance
Data Source
AI summary
Techniques to facilitate passive detection of forged web browsers are disclosed herein. In at least one implementation, web traffic between a web server and a client is monitored, and a hypertext transfer protocol (HTTP) header transmitted by the client is processed to determine a type of web browser associated with the client. Attribute data points for the client are generated based on fields in the HTTP request header transmitted by the client and connection behavior of the client with the web server. The attribute data points for the client are then compared with predetermined attribute data points for the type of web browser associated with the client to determine if the client is a genuine web browser of the type of web browser associated with the client.