QR Code Phishing Detection via White Color Level Analysis
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Solution Overview
Problem
Current technologies lack effective methods to detect and prevent phishing attacks using QR Codes, as they are easily replicable and difficult to identify, leading to potential data theft from users.
Innovation Solution
A method involving scanning QR Codes row by row and column to compare white color levels of squares, using RGB components, and applying a dynamic multiplier to compensate for shading, which generates a phishing notifier if differences exceed a threshold, blocking malicious URL access and alerting users.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If QR Codes are used to carry information and enable mobile access, then usability and information capacity are improved, but vulnerability to phishing attacks increases
Solution Approach 1:
The patent applies color changes by detecting variations in white color levels across different squares of the QR code. Phishing QR codes often have uniform coloring, while legitimate ones may show natural variations. The system measures the standard deviation of white color levels and compares it against thresholds to identify suspicious patterns, thereby detecting phishing attempts while maintaining QR code functionality.
Solution Approach 2:
The patent replaces manual visual inspection with automated image processing and statistical analysis. Instead of requiring users to manually examine QR code characteristics, the system uses computational methods to scan, measure, and compare color levels across all squares, automatically identifying phishing codes through algorithmic detection of abnormal color uniformity.
2Ease of manufacture
If simple QR Code structures are used for easy creation and reading, then ease of manufacture and operation are improved, but detectability of phishing becomes more difficult
Solution Approach 1:
The patent segments the QR code into individual squares and analyzes each one's color characteristics separately. By dividing the QR code matrix into discrete units and measuring white color levels for each square, the system can detect subtle variations and uniformity patterns that indicate phishing, while maintaining compatibility with standard QR code structures.
Solution Approach 2:
The patent introduces an intermediary analysis layer between the QR code visual appearance and the phishing detection decision. This intermediary consists of statistical measures (standard deviation calculations) and threshold comparison mechanisms that objectively evaluate color level variations, providing a reliable bridge between simple QR code structure and secure detection without requiring complex visual analysis.
3Reliability
If comprehensive phishing detection methods are implemented, then security and reliability are improved, but device complexity and processing requirements increase
Solution Approach 1:
The patent applies partial action by focusing detection efforts specifically on measuring white color levels and calculating standard deviations, rather than performing comprehensive analysis of all QR code characteristics. This targeted approach achieves reliable phishing detection through a limited set of meaningful measurements, avoiding the complexity of analyzing every possible visual and structural aspect of QR codes.
Data Source
AI summary
A method and a system for detecting phishing of a matrix barcode is provided. The matrix barcode comprises colored and white squares in rows and columns. The method comprises scanning the matrix barcode row by row and column by column resulting in received squares, storing a corresponding white color level for each received white square, and comparing the white color levels of the received white squares couple-wise.