User Activity-Triggered URL Scan for Phishing Mitigation
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing security systems face challenges in effectively and efficiently mitigating phishing attacks, particularly due to the dynamic nature of phishing websites that frequently change their URLs, leading to delays and user frustration, and the need for continuous analysis that disrupts the browsing experience.
Innovation Solution
A user activity-triggered URL scan system that pauses commands sending sensitive information to unknown websites, checks local and cloud-based reputations, and performs deep analysis only when necessary, such as during an HTML POST operation, to streamline the user experience and reduce false positives.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If continuous URL scanning is performed to detect phishing sites, then security reliability is improved, but user browsing experience deteriorates due to delays and disruptions
Solution Approach 1:
The system performs preliminary actions by checking local reputation cache and cloud-based reputation services before blocking any URLs. This preliminary checking mechanism allows the system to quickly identify known phishing sites without disrupting legitimate browsing, while only performing deep analysis when necessary based on reputation scores.
Solution Approach 2:
The system dynamically adjusts its scanning behavior based on the reputation score of each URL. For high-reputation URLs, no scanning is performed allowing seamless browsing. For low-reputation URLs, the system performs deep analysis. This dynamic approach resolves the contradiction by making the scanning intensity adaptive rather than static.
2Measurement precision
If deep analysis is performed on all URLs to ensure security, then detection precision is improved, but processing time increases causing user frustration
Solution Approach 1:
The system applies partial action by performing only lightweight reputation checks on all URLs, and reserving deep analysis for only those URLs that fall below a threshold reputation score. This selective approach ensures high detection precision for suspicious URLs while minimizing time loss for legitimate browsing.
Solution Approach 2:
The system implements local quality by applying different levels of analysis to different URLs based on their reputation characteristics. High-reputation URLs receive minimal processing (local optimization for speed), while low-reputation URLs receive intensive analysis (local optimization for accuracy). This resolves the contradiction by making analysis intensity location-specific rather than uniform.
3Adaptability or versatility
If phishing websites are frequently updated with new URLs, then adaptability of attackers is improved, but existing security systems fail to detect them due to delays in updating blocklists
Solution Approach 1:
The system implements feedback mechanisms by continuously monitoring URL reputation scores from cloud-based services and updating local caches in real-time. When a URL's reputation changes, the system immediately receives feedback and adjusts its blocking behavior accordingly, ensuring rapid detection of newly deployed phishing sites without relying on periodic blocklist updates.
4Reliability
If reputation checking is performed for every command sending sensitive information, then security coverage is improved, but system complexity increases
Solution Approach 1:
The system applies universality by using a single reputation checking mechanism that serves multiple functions: blocking phishing sites, filtering malicious commands, and providing security alerts. This multi-functional approach improves security coverage without proportionally increasing system complexity, as the same core infrastructure handles diverse security tasks.
Data Source
AI summary
A computer-implemented method protects a user from phishing attacks by managing commands initiated via a web browser. The method includes determining that a user has initiated a command that will send information to a target website, where the information belongs to a class that may include sensitive user data and the target website lacks a device-local phishing reputation. After this determination, the command is paused before the information is sent. While paused, a new reputation for the target website is obtained, and the command is blocked if the new reputation is deemed not safe, thereby preventing potential phishing threats.