Local Trusted URL Database for False Positive Reduction
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Solution Overview
Problem
Current security applications face inconvenience due to false positives where reputation systems misclassify safe URLs as malicious, necessitating more effective methods to minimize false positives without compromising security.
Innovation Solution
A method utilizing a local database of trusted URLs on the client computer, where URLs are qualified based on user visits, metadata analysis, and predefined criteria, to override reputation data from servers, thereby reducing false positives and allowing access only when safety thresholds are met.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If reputation systems are used to evaluate URL safety, then security protection is improved, but false positives increase causing inconvenience
Solution Approach 1:
The system performs preliminary actions by pre-establishing a local database of trusted URLs based on user visit history and metadata analysis before actual security evaluation is needed. This preliminary classification allows the system to make faster, more accurate decisions during runtime without relying solely on external reputation systems.
Solution Approach 2:
The patent introduces an intermediary mechanism - a local database of trusted URLs that mediates between the user's access requests and external reputation systems. This intermediary layer filters out false positives by cross-referencing with locally stored trusted URL information before blocking access.
2Reliability
If strict reputation checking is performed, then security is improved, but access speed decreases due to additional validation steps
Solution Approach 1:
The system performs preliminary classification of URLs into trusted and untrusted categories based on user visit history and metadata analysis before actual access decisions are made. This preliminary action reduces the number of strict reputation checks needed during runtime, improving access speed while maintaining security.
Solution Approach 2:
The patent applies partial action by performing reputation checking only on URLs that are not in the local trusted database, rather than checking all URLs with the same strictness. This selective approach maintains security for unknown URLs while allowing faster access to known trusted sites.
3Ease of operation
If local database of trusted URLs is implemented, then false positives are reduced, but device complexity increases
Solution Approach 1:
The system implements self-service by automatically maintaining the local trusted URL database through user visit tracking and metadata analysis. The system serves itself by using its own operational data (user visits, page metadata) to build and update the trusted URL list without requiring external intervention or complex manual configuration.
Solution Approach 2:
The local database serves multiple functions: it stores trusted URL information, tracks user visit history, maintains metadata for classification, and provides fast lookup during access decisions. This multi-functionality reduces the need for separate systems and minimizes overall complexity despite the added database component.
Data Source
AI summary
In accordance with an example embodiment of the present invention, there is provided a method comprising: maintaining a local database of trusted uniform resource locators (URL) where an URL is qualified to said database based on fulfilling predetermined criteria; detecting a request to access a uniform resource locator (URL); obtaining reputation data for the URL from a reputation server or from a local reputation scanner; comparing the obtained reputation data of the requested URL with the reputation data of the requested URL that is stored in the local database of trusted URLs if any; if there is a conflict between the reputation data obtained and the reputation data stored in the local database of trusted URLs, using the reputation data stored in the local database of trusted URLs to determine whether access to the URL is allowed.