Automated Website Legitimacy Scoring System
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Solution Overview
Problem
Existing methods for detecting fraudulent or malicious enterprises online are costly, manual, and inefficient, as they struggle to keep pace with the rapid replication and distribution of illegitimate content across multiple IP addresses and websites by large-scale criminal operations.
Innovation Solution
A computerized system that analyzes website content using machine and non-machine learning methods, pattern recognition, and enrichment with domain ownership and geolocation data to determine legitimacy by assigning scores based on analysis, correlating data points, and identifying patterns indicative of illegitimate content, with automatic and manual review processes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual domain name seizure methods are used to detect fraudulent websites, then detection accuracy may be maintained, but the process becomes costly and inefficient
Solution Approach 1:
The system performs self-service by automatically analyzing website content, calculating legitimacy scores, and identifying fraudulent sites without requiring manual intervention. The automated analysis engine continuously monitors and evaluates websites, making the detection process self-sufficient and highly efficient.
Solution Approach 2:
The patent replaces manual mechanical processes (human analysts physically examining websites) with automated computational systems. The analysis engine uses algorithmic methods to evaluate website content, replacing the need for human manual inspection while maintaining or improving detection accuracy.
2Productivity
If automated programmatic replication is used by criminal enterprises to distribute fraudulent content, then productivity of fraudulent operations increases, but detection capability remains insufficient
Solution Approach 1:
The system performs preliminary actions by pre-establishing a database of legitimate website characteristics and legitimacy scoring criteria before fraudulent content appears. This allows the system to quickly evaluate new websites against known legitimate patterns, enabling reliable detection even as fraudulent operations scale.
Solution Approach 2:
The system implements feedback mechanisms where detection results and analysis data are continuously fed back into the legitimacy database. This allows the system to learn from new fraudulent patterns and update its detection criteria, maintaining reliability as criminal enterprises evolve their methods.
3Measurement precision
If extensive manual review processes are implemented to verify website legitimacy, then measurement precision improves, but loss of time increases significantly
Solution Approach 1:
The system applies partial action by performing automated analysis on all websites and reserving manual review only for cases where the automated legitimacy score falls within a uncertain range. This reduces the time loss significantly while maintaining precision by applying manual review only when necessary.
Solution Approach 2:
The patent changes the parameter of verification from a binary manual-review-or-not approach to a continuous legitimacy scoring system. Websites are assigned scores based on multiple analysis parameters, allowing the system to automatically handle clear cases and only involve manual review for borderline cases, thereby reducing time loss while maintaining accuracy.
Data Source
AI summary
A computer system and method for determining the legitimacy of a website determines the presence of a relationship between a received website and at least one known illegitimate website. When such a relationship is detected, the received website is determined to be illegitimate and corresponding action may be taken.