Firewall Policy Inspection Anomaly Detection
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Solution Overview
Problem
Existing firewall policy inspection technologies fail to efficiently detect and display anomaly rules, such as shadowing, redundancy, correlation, and generalization anomalies, between intrusion prevention rules, and do not indicate risk levels effectively, leading to increased effort and potential security vulnerabilities.
Innovation Solution
A firewall policy inspection apparatus and method that includes an intrusion prevention rule obtainment unit, an anomaly rule detection unit, and a screen display unit to detect and display anomaly rules in relationships between intrusion prevention rules, indicating them in colors based on risk levels, allowing for easier inspection of firewall policies.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual detection of anomaly rules is performed by a manager, then detection capability is maintained, but effort and time requirements increase significantly
Solution Approach 1:
The patent replaces the manual mechanical inspection process with an automated computer-based system that uses algorithms to detect anomaly rules. The anomaly rule detection unit automatically analyzes firewall policies and identifies shadowing, redundancy, correlation, and generalization anomalies without human intervention, thereby eliminating the time-consuming manual inspection while maintaining detection accuracy.
Solution Approach 2:
The system enables self-service by allowing the firewall policy inspection to be performed automatically by the computer itself rather than requiring external human management. The anomaly detection unit continuously monitors and inspects rules autonomously, freeing managers from the burden of manual detection while ensuring consistent and reliable anomaly identification.
2Measurement precision
If manual detection of anomaly rules is performed by a manager, then detection capability is maintained, but error rates increase due to human factors
Solution Approach 1:
The patent eliminates human error by replacing manual detection with an automated computer-based anomaly detection unit. This system applies consistent algorithmic logic to identify shadowing, redundancy, correlation, and generalization anomalies, ensuring reliable and accurate detection without the variability and errors inherent in human inspection.
Solution Approach 2:
The system incorporates feedback mechanisms where the anomaly detection unit continuously analyzes firewall policies and provides structured output about detected anomalies. This automated feedback loop ensures consistent application of detection rules and maintains high reliability by systematically identifying and reporting anomaly patterns without human intervention.
3Adaptability or versatility
If conventional inspection methods are used, then existing functionality is maintained, but anomaly rules cannot be effectively detected among multiple intrusion prevention rules
Solution Approach 1:
The patent segments the complex task of firewall policy inspection into distinct anomaly types: shadowing anomalies, redundancy anomalies, correlation anomalies, and generalization anomalies. Each type is detected by specific detection logic within the anomaly detection unit, making the overall complex inspection process manageable and effective by breaking it down into targeted detection segments.
Solution Approach 2:
The patent introduces a new dimension of inspection by analyzing relationships between multiple intrusion prevention rules simultaneously. Rather than examining rules in isolation, the system evaluates inter-rule relationships to detect anomalies, adding a relational dimension to the inspection process that enables effective detection among multiple rules.
4Measurement precision
If detailed anomaly detection is implemented, then detection accuracy improves, but system complexity increases
Solution Approach 1:
The patent manages complexity by segmenting anomaly detection into four distinct anomaly types with specific detection logic for each. This segmentation allows the system to achieve high detection accuracy through specialized algorithms for each anomaly type while organizing the overall system structure in a manageable, modular way that reduces operational complexity.
Data Source
AI summary
A firewall policy inspection apparatus and method is provided. The firewall policy inspection apparatus includes an intrusion prevention rule obtainment unit for obtaining intrusion prevention rules from a target firewall policy. An anomaly rule detection unit detects an anomaly rule in a relationship between the intrusion prevention rules. A screen display unit displays an anomaly rule graph on a screen using results of the detection.