Short URL Redirection Analysis for Phishing Domain Detection
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Solution Overview
Problem
Existing phishing detection solutions are inadequate in identifying phishing attempts concealed behind shortened URLs, as they lack comprehensive methodologies to proactively analyze redirections from short URLs, leaving organizations vulnerable to sophisticated attacks.
Innovation Solution
A method involving short URL detection techniques such as provider enumeration, backlink analysis, link unshortening, search engine analysis, and URL shortener API analysis is employed to systematically identify and classify phishing attempts by analyzing redirections from short URLs to candidate look-alike domains.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional reactive phishing detection methods (blacklisting, content analysis) are used, then implementation simplicity is maintained, but detection effectiveness against short URL phishing attacks deteriorates
Solution Approach 1:
The system performs preliminary actions by proactively generating candidate look-alike domains before phishing attacks occur, and pre-analyzing short URL redirection patterns. This allows the system to detect phishing attempts before they reach users, rather than reacting after detection. The methodology includes pre-computing domain similarity metrics and maintaining ready-to-use detection rules for short URL patterns.
Solution Approach 2:
The detection system is segmented into multiple independent modules: short URL detection techniques, look-alike domain generation, redirection analysis, and classification components. Each module operates independently and can be executed in parallel, reducing overall system complexity while improving detection effectiveness. The segmentation allows for specialized optimization of each component.
2Reliability
If multiple short URL detection techniques are executed in parallel, then phishing detection completeness is improved, but computational resource consumption increases
Solution Approach 1:
The system applies partial action by selectively executing detection techniques based on risk assessment. Not all detection techniques are run for every short URL - instead, the system prioritizes techniques based on domain similarity scores, URL patterns, and threat intelligence data. This reduces computational overhead while maintaining high detection completeness for actual phishing threats.
Solution Approach 2:
Computational resources are optimized through preliminary filtering steps that identify high-risk short URLs before applying full detection analysis. The system pre-processes URLs using lightweight heuristics to filter out low-risk cases, reserving intensive computational resources only for suspicious URLs that require deeper analysis.
3Measurement precision
If comprehensive short URL redirection analysis is performed, then phishing threat identification accuracy is improved, but analysis time increases
Solution Approach 1:
The analysis system applies local quality by focusing computational effort on specific critical attributes of short URLs and redirect patterns rather than uniformly analyzing all aspects. The methodology identifies and prioritizes key indicators such as domain similarity metrics, redirection chain depth, and timestamp patterns, allocating more analysis resources to these high-value attributes while reducing effort on less discriminatory features.
Solution Approach 2:
The system performs partial analysis by implementing multi-stage detection where not all analysis techniques are applied to every URL. High-confidence detections from initial analysis stages allow the system to skip subsequent verification stages for clear cases, reducing overall analysis time while maintaining high accuracy through selective application of comprehensive analysis only when needed.
Data Source
AI summary
Systems and methods include receiving a customer domain from a user via a user device; parsing a plurality of candidate look-alike domains based on the customer domain; executing at least one detection technique selected from a plurality of short URL detection techniques to determine whether one or more short URLs redirect to one of the plurality of candidate look-alike domains; and in response to determining, by the at least one detection technique, that the one or more short URLs redirect to one of the plurality of candidate look-alike domains, classifying that candidate look-alike domain as a phishing attempt.