Dynamic Network Resource Categorization Interval Adjustment
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Solution Overview
Problem
Existing methods for categorizing network resources are computationally expensive and impractical for frequent analysis due to the fluid nature of network resources, which are subject to frequent updates and changes, making it challenging to provide adequate security from malware and undesirable content.
Innovation Solution
A system with a categorization engine and a categorization interval adjustment engine that analyzes network resource properties to assign categories and dynamically adjusts re-categorization intervals based on previous results, reducing intervals for malicious content and increasing them for non-malicious content, ensuring timely updates and efficient resource management.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If comprehensive analysis of network resources is performed, then security detection accuracy is improved, but processing time and computational cost increase
Solution Approach 1:
The system dynamically adjusts the categorization interval for each network resource based on its security risk profile and historical behavior. High-risk resources receive more frequent monitoring, while low-risk resources are monitored less frequently, optimizing the balance between detection accuracy and processing time
Solution Approach 2:
The system changes the monitoring parameters (categorization interval) based on the security characteristics of each network resource. Resources showing malicious behavior patterns have their monitoring frequency increased, while benign resources have reduced monitoring, adapting the system's operational parameters to actual security needs
2Reliability
If frequent re-categorization of network resources is performed, then security response to changes is improved, but system performance and resource utilization deteriorate
Solution Approach 1:
The system applies different monitoring frequencies to different network resources based on their individual security characteristics. Instead of uniform frequent monitoring, each resource receives customized attention proportional to its risk level, maintaining security reliability while preserving system performance
Solution Approach 2:
The system performs comprehensive analysis only when necessary - specifically when security risks are detected or suspected. For the majority of benign resources, less frequent and less intensive monitoring is applied, avoiding excessive processing while maintaining adequate security coverage
3Device complexity
If uniform re-categorization interval is applied to all network resources, then system simplicity is maintained, but security effectiveness for different resource types deteriorates
Solution Approach 1:
The system assigns different categorization intervals to different network resources based on their security profiles, content types, and historical behavior. This localized customization improves security effectiveness without requiring complex manual configuration, as the system automatically determines appropriate intervals for each resource
4Measurement precision
If comprehensive content analysis is performed on all network resources, then malicious content detection is improved, but computational resource consumption increases
Solution Approach 1:
The system performs comprehensive content analysis only for resources that exhibit suspicious characteristics or have been previously identified as high-risk. For the majority of benign resources, lighter monitoring approaches are used, significantly reducing computational energy consumption while maintaining high malware detection accuracy through targeted deep analysis
Data Source
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AI summary
System and method for categorizing a plurality of network resources. Collected properties of a network resource are analyzed to determine applicability of various predefined categories to that network resource. At least one category from among the predefined categories is assigned to that network resource according to a determination of applicability of the at least one category to the network resource. A resource-specific time interval for re-categorizing each one of the network resources is dynamically adjusted based on a plurality of previous categorization results for that network resource, such that different network resources will be associated with correspondingly different re-categorization intervals.