Scheduled Web Resource Malware Scanning
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Solution Overview
Problem
Conventional malware scanning systems face challenges in effectively checking web resources for malware, especially when resources are inaccessible externally, and require significant time and resources to scan large numbers of web pages, with limitations in detecting threats before they spread due to restrictions and the need for user authentication.
Innovation Solution
A system for scheduled malware scanning of web resources that configures scan parameters, including frequency and depth, using a database to track user visits and authorization, allowing for automated scanning without additional client applications, employing both signature and heuristic methods to identify malware and vulnerabilities.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional malware scanning systems scan all web pages, then detection precision is improved, but loss of time increases significantly
Solution Approach 1:
The patent applies partial action by scanning only a representative subset of web pages rather than all pages. The system selects a limited number of pages (e.g., 10-20 pages) from each website to scan for malware, which significantly reduces scanning time while maintaining effective detection coverage. This approach balances thoroughness with efficiency by focusing resources on sampling key pages.
Solution Approach 2:
The system performs preliminary actions by maintaining an updated database of known malware signatures and website information before actual scanning occurs. The database is pre-populated with malware patterns, website structures, and risk assessments, enabling faster on-site scanning without needing to analyze every page from scratch.
2Reliability
If user authentication is required for scanning, then reliability of detection is improved, but ease of operation deteriorates
Solution Approach 1:
The system implements self-service by automatically managing authentication credentials and session management. The scanner stores and uses saved login information, cookies, and session tokens to access protected websites without requiring manual user intervention for each authentication step. This maintains reliable authenticated access while eliminating the operational burden of manual login.
Solution Approach 2:
The patent uses an intermediary approach by introducing a credential management layer between the user and the scanning process. The system securely stores authentication data and automatically supplies credentials when needed, acting as an intermediary that handles the complexity of authentication while presenting a simple interface to users.
3Measurement precision
If scanning frequency is increased, then detection precision is improved, but use of energy increases
Solution Approach 1:
The system applies periodic action by scanning websites at scheduled intervals rather than continuously. It determines optimal scan frequencies based on website update rates, risk levels, and resource constraints, performing scans at regular periods (e.g., daily, weekly, or monthly) rather than continuously. This maintains detection effectiveness while significantly reducing energy consumption compared to continuous scanning.
Solution Approach 2:
The patent implements dynamic scanning frequency adjustment based on multiple factors including website risk classification, recent update activity, and detected threat levels. High-risk or frequently updated sites receive more frequent scans, while low-risk sites are scanned less often, optimizing energy usage while maintaining appropriate detection precision for each target.
4Measurement precision
If scanning depth is increased, then detection precision is improved, but device complexity increases
Solution Approach 1:
The system applies segmentation by dividing the scanning process into distinct modules and layers: database lookup, signature matching, heuristic analysis, and behavioral detection. Each module handles a specific aspect of malware detection, allowing the system to achieve high detection precision through specialized sub-components rather than a single complex monolithic scanner.
Data Source
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AI summary
A method and system for identification of malware threats on web resources. The system employs a scheduled antivirus (AV) scanning of web resources. The scheduled scanning of web resources allows to create malware check lists and to configure access to web resources. Frequency and depth of inspection (i.e., scan) are determined for each web resource. The user identifiers are used for scheduled AV scanning of web resources. The system allows for scanning a web resource based on selected configurations without using additional client applications.