HTTP Request Header Anomaly Detection via Browser Signature Analysis
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Solution Overview
Problem
Current software products fail to detect fraudulent activity by scanning incoming HTTP request headers for anomalies, as each browser has a unique 'signature' and order of headers, making it difficult to distinguish between legitimate and altered requests.
Innovation Solution
A method that compares incoming HTTP request headers with a correct set for each browser type to detect anomalies, using a web server to identify browser type and take corrective action, such as denying access, by analyzing headers like ACCEPT, ACCEPT_ENCODING, ACCEPT_LANGUAGE, CONNECTION, HOST, REFERER, and USER_AGENT.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If software products scan incoming HTTP request headers to detect fraudulent activity, then fraud detection capability is improved, but device complexity increases due to the need to analyze multiple browser-specific header signatures and orders
Solution Approach 1:
The patent transforms the complex task of analyzing multiple header parameters into a simpler parameter-based approach by focusing on the order position of specific headers. Instead of analyzing the content and structure of multiple headers simultaneously, the system extracts a key parameter (header order position) that varies by browser type and uses this single parameter for fraud detection, thereby reducing system complexity while maintaining detection capability
Solution Approach 2:
The patent extracts the essential fraud-detecting element from the complex header analysis by isolating the header order position as the critical indicator. Rather than processing all header contents, the system extracts and analyzes only the position of specific headers (like Referer, User-Agent, Accept-Encoding) which serves as a fingerprint for legitimate vs. fraudulent requests, simplifying the overall detection mechanism
2Measurement precision
If the system analyzes all incoming HTTP request headers in detail to distinguish legitimate from fraudulent requests, then measurement precision is improved, but processing time increases
Solution Approach 1:
The patent extracts only the critical header order position information needed for fraud detection, ignoring other header contents. This selective extraction maintains high detection accuracy by focusing on the most discriminative feature (header sequence) while dramatically reducing the processing time required compared to analyzing all header parameters in detail
Solution Approach 2:
The patent applies partial action by analyzing only a subset of header parameters (specifically the order positions of key headers) rather than performing exhaustive analysis of all headers. This partial analysis approach achieves sufficient detection precision for fraud identification while minimizing processing time and computational resources required
Data Source
AI summary
A system and a method are disclosed for detecting an unacceptable HTTP requests by scanning the headers of the HTTP requests.