Security Rule Placement Optimization via Threat Analysis
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Solution Overview
Problem
Current network security management systems require manual, labor-intensive processes for configuring policies to mitigate cyber threats, which are inefficient and ill-equipped to handle the increasing sophistication of cyberattacks.
Innovation Solution
An integrated security management system that includes a threat control module and a rule analysis module to optimize the placement of security rules within security devices, allowing administrators to interact with graphical representations of threats and automatically generate and deploy optimized security policies.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If manual configuration processes are used for security policies, then administrators can configure protection systems, but the process becomes labor-intensive and inefficient
Solution Approach 1:
The system automatically generates security policies by monitoring network traffic and detecting threats itself, without requiring manual administrator intervention for each policy creation. The security device performs self-analysis of traffic patterns and self-configures appropriate security rules, transforming the manual configuration process into an automated self-service system.
Solution Approach 2:
The patent replaces the mechanical manual configuration process with an automated electronic system that uses machine learning and pattern recognition algorithms to analyze network traffic and generate security policies automatically, substituting human administrative work with computational processes.
2Productivity
If automated rule generation is implemented, then policy configuration becomes efficient, but rule placement optimization is needed to avoid anomalies
Solution Approach 1:
The system implements a feedback mechanism where the security device continuously monitors the performance and effectiveness of generated security rules, analyzes anomalies in rule execution, and uses this feedback to optimize rule placement and ordering. This closed-loop feedback ensures that automated rule generation maintains high reliability through continuous refinement based on actual system performance.
Solution Approach 2:
The system performs preliminary analysis of network traffic patterns and threat characteristics before generating security rules, and conducts preliminary optimization of rule placement order to prevent anomalies before they occur. By performing these actions in advance rather than reactively, the system ensures reliable rule execution from the start.
Data Source
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AI summary
Techniques are described for optimizing the placement of automatically generated rules within security policies. An administrator may, for example, interact with the graphical representation of rules rendered by the threat control module and, responsive to the interaction, the system may determine an optimal placement for the created rule in the list of rules for the identified security device based on either the existence of anomalies or threat IP data and/or advanced security parameters. In this way, the system allows administrators to configure rules with the most optimal sequence to detect threats.