Dynamic Cybersecurity Rule Prioritization for Threat Detection
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Solution Overview
Problem
Conventional rule-based cyber-security software struggles with inefficient resource utilization and delayed threat detection due to static threat detection rules that do not account for real-time changes in the threat landscape, leading to potential failures in detecting cyberattacks, especially in targeted scenarios.
Innovation Solution
A system that dynamically reprioritizes analytic rules based on cyber-security intelligence from network devices, using metadata to reorder and re-weight detection rules for improved resource efficiency and faster threat detection, allowing for timely adaptation to evolving threats.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If static threat detection rules are used with fixed processing order, then system stability is maintained, but threat detection speed and resource efficiency deteriorate due to inability to adapt to real-time changes in threat landscape
Solution Approach 1:
The patent implements dynamic rule prioritization where the processing order of threat detection rules is automatically adjusted based on real-time metadata from the threat landscape. Rules are re-ranked dynamically without changing the rule set itself, allowing the system to adapt to emerging threats while maintaining operational stability.
Solution Approach 2:
The system changes the priority parameter of existing rules based on metadata analysis rather than modifying the rules themselves. This allows dynamic adaptation by adjusting the processing order parameter while keeping the rule logic intact, reducing complexity compared to creating new rules continuously.
2Reliability
If comprehensive threat detection analysis is performed on all rules, then detection thoroughness is improved, but resource utilization deteriorates due to processing less critical rules
Solution Approach 1:
The system performs partial analysis by focusing computational resources on high-priority rules identified through metadata-driven prioritization. Less critical rules are processed with reduced intensity or deferred, achieving effective threat detection while conserving computational resources during normal operation.
Solution Approach 2:
The patent implements continuous metadata collection and analysis to maintain an updated priority ranking of rules. This continuous feedback loop ensures that computational resources are consistently directed toward the most relevant threats without requiring complete re-analysis of all rules, optimizing resource utilization while maintaining detection reliability.
3Measurement precision
If threat detection rules are updated frequently to reflect current threats, then detection accuracy is improved, but system stability deteriorates due to constant rule changes
Solution Approach 1:
The system dynamically adjusts rule prioritization based on metadata from the current threat landscape rather than frequently updating the rule set itself. This dynamic re-ranking maintains detection accuracy by responding to new threats while preserving rule set stability by keeping the underlying rules unchanged.
Solution Approach 2:
The patent creates a dynamic priority ranking layer that copies and reorders existing rules based on current threats. This virtual copying approach allows the system to adapt to new threats through metadata-driven prioritization without modifying or frequently updating the original rule set, maintaining both accuracy and stability.
4Ease of operation
If legacy rule processing order is maintained for consistency, then processing predictability is improved, but threat detection timeliness deteriorates due to delayed detection of critical threats
Solution Approach 1:
The system transitions from static to dynamic rule prioritization where the processing order adapts in real-time based on metadata analysis. Critical threats automatically move to higher priority positions in the processing queue, reducing detection delay while maintaining predictable processing through systematic metadata-driven re-ranking rather than arbitrary changes.
Solution Approach 2:
The patent implements feedback mechanisms where metadata from threat detection results and the current threat landscape continuously inform rule prioritization adjustments. This feedback loop ensures that rules detecting current critical threats are automatically elevated in priority, improving detection timeliness while maintaining operational predictability through consistent feedback-driven re-ranking.
Data Source
AI summary
A system and computerized method for generating an improved cyber-security rule ordering for cyber-security threat detection or post-processing activities conducted by a rules-based cyber-security engine deployed within a network device is described. Herein, historical metadata associated with analytics conducted on incoming data by a rule-based cyber-security engine and in accordance with a plurality of rules is described. These rules are arranged in a first ordered rule sequence. The historical metadata is analyzed to determine one or more salient rules from the plurality of rules. The plurality of rules are reprioritized by at least rearranging an order to a second ordered rule sequence with the one or more salient rules being positioned toward a start of the second ordered rule sequence. Thereafter, the rule-based cyber-security engine operates in accordance with the reprioritized rule set that is arranged in the second ordered rule sequence to achieve improved performance.