Web Page Impersonation Detection via Certificate and Image Analysis
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Solution Overview
Problem
Existing technologies struggle to effectively detect and prevent impersonated web pages that mimic trustworthy entities, leading to phishing attacks and potential data breaches.
Innovation Solution
A system that combines multiple techniques to validate ownership of a web page, including analyzing user credentials, images, web site behavior, digital signatures, and certificates, to identify potential impersonation attempts.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If multiple validation techniques are combined to detect impersonated web pages, then detection reliability is improved, but system complexity increases
Solution Approach 1:
The detection system is divided into multiple independent validation modules, each responsible for a specific aspect of verification. The parser module handles HTML structure analysis, the certificate validator module handles digital certificate verification, and the behavior analyzer module handles runtime behavior detection. This segmentation allows each module to specialize in one technique while collectively providing comprehensive detection coverage, resolving the contradiction between reliability and complexity.
Solution Approach 2:
The patent combines multiple detection techniques (parser validation, certificate verification, behavior analysis, image recognition) into a unified detection system. These previously separate detection methods are merged to work together synergistically, where the output of one module feeds into another, creating a more reliable detection system without requiring completely separate solutions for each technique.
2Measurement precision
If comprehensive validation of web page ownership is performed, then detection precision is improved, but processing time increases
Solution Approach 1:
The system performs preliminary validation actions by analyzing static characteristics of the web page (HTML structure, certificate validity, domain registration information) before executing more time-consuming behavior analysis. This allows the system to quickly identify obviously malicious pages through simple checks while reserving deeper analysis for pages that pass initial screening, thus maintaining high precision while reducing overall processing time.
Solution Approach 2:
The detection system dynamically adjusts its validation depth based on the complexity of the web page being analyzed. For simple pages, the system performs only necessary validation checks, while for complex pages with multiple validation failures or suspicious behaviors, the system escalates to more comprehensive analysis. This dynamic approach ensures detection precision is maintained while minimizing processing time for straightforward cases.
Data Source
AI summary
Identifying a malicious web page that impersonates a legitimate web page, including extracting HMTL source and a certificate for a specified web page, parsing the extracted HTML to identify objects, forms, links, templates, images and logos embedded in the HTML, and determining whether or not the HTML source harvests user credentials. If the determining is negative, then marking the specified web page as clean. If the determining is affirmative, then verifying the origin and ownership of the extracted certificate by examining its digital signature to determine a possibility of an impersonation attempt, applying image recognition to the identified images and logos, and comparing the identified images and logos to known images and brand logos of the certificate owner. If the comparing is affirmative, then mark the web page as clean. If the comparing is negative, then mark the web page as suspicious and block the web page from being accessed.