Webpage Threat Detection Using Visual Identifiers and Access Control
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Solution Overview
Problem
Internet users are frequently at risk from webpages configured to extract user data for illegal, disreputable, or otherwise objectionable purposes, which mimic legitimate entities, making it difficult to identify and protect against deceptive electronic interactions.
Innovation Solution
A system and method for detecting and mitigating network-based computing threats by crawling webpages, capturing images, determining identifiers, and controlling access based on comparisons with learned identifiers, using self-learning modules and threat mitigation systems to identify and block phishing attempts.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Object-affected harmful factors
If webpages are configured to mimic legitimate entities with logos, language, and protocols, then the deception becomes more convincing and harder to detect, but the ability to extract user data for illicit purposes increases
Solution Approach 1:
The system performs preliminary crawling and analysis of webpages to extract identifiers and detect data extraction mechanisms before users are exposed to the phishing sites. By pre-processing and storing information about potential threats, the system can quickly compare incoming webpages against known patterns and block malicious sites before they can harm users.
Solution Approach 2:
The system introduces an intermediary layer between the user and the webpage through browser integration. This intermediary automatically analyzes webpages, compares extracted identifiers against known legitimate entities, and blocks access to phishing sites without requiring user awareness or intervention. The intermediary acts as a shield that transparently protects users from deceptive sites.
2Measurement precision
If manual monitoring and analysis of webpages is performed to detect phishing attempts, then detection accuracy can be maintained, but the system requires significant human intervention and cannot scale effectively
Solution Approach 1:
The system implements self-service through automated crawling, identifier extraction, and comparison mechanisms. The browser integration automatically monitors webpages, extracts identifiers, compares them against stored data about legitimate entities, and blocks phishing sites without human intervention. This automation maintains detection accuracy while eliminating the need for manual monitoring.
Solution Approach 2:
The system replaces manual mechanical analysis with automated computational processes. Instead of human analysts examining webpages, the system uses automated crawlers to extract identifiers, computational algorithms to compare identifiers against known entities, and programmatic blocking mechanisms. This substitution maintains or improves detection accuracy while enabling scalable automation.
3Reliability
If comprehensive crawling and analysis of all webpages is performed to identify phishing sites, then detection recall is improved, but the computational resources and time required increase significantly
Solution Approach 1:
The system extracts only the most critical identifying features from webpages rather than analyzing entire pages. By focusing on specific identifiers such as logos, domain names, and key textual elements, the system achieves high detection recall while minimizing computational overhead. This selective extraction approach maintains reliability without requiring exhaustive analysis of all webpage content.
Solution Approach 2:
The system performs partial analysis by focusing on key identifier extraction rather than comprehensive webpage examination. By analyzing only the most discriminative features necessary for phishing detection, the system achieves sufficient recall to identify malicious sites while maintaining processing efficiency. The system does what is necessary (extracting identifiers) without doing what is excessive (analyzing all content).
Data Source
AI summary
A system and method of controlling access to a webpage is provided. A plurality of webpages are crawled respectively at a plurality of network addresses on a network. A plurality of images of the plurality of webpages are captured. A plurality of identifiers are determined based on the plurality of images and the plurality of network addresses. A particular webpage at a particular network address is detected, and it is determined that the particular webpage includes a mechanism for user data extraction. A particular image of the particular webpage is captured responsive to the determining that the particular webpage includes the mechanism for user data extraction. A particular identifier is determined based on the particular image and the particular network address. The particular identifier is compared to the plurality of identifiers, and access by a particular computing device to the particular webpage is controlled based on the comparing.