Packet Filtering Re-Evaluation Using Updated Threat Intelligence
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Solution Overview
Problem
Existing network security systems face challenges in applying updated cyber threat intelligence to previous packet filtering data, leading to inefficiencies and potential loss of important data due to the volume and complexity of cyber threats, lack of resources, and disincentives for retroactive application of updated threat intelligence.
Innovation Solution
A cyber threat analysis system applies updated cyber threat intelligence to packet filtering output data generated based on earlier intelligence, identifying relevant data using earlier intelligence to guide the application of new criteria, thereby enhancing detection and prevention of cyber threats.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If updated cyber threat intelligence is applied to all previous packet filtering data, then threat detection accuracy is improved, but resource consumption and processing time increase significantly
Solution Approach 1:
The system segments packet filtering data by associating each data record with a specific filtering rule identifier. This allows the system to divide the large volume of historical data into manageable segments that can be selectively re-evaluated based on updated threat intelligence, rather than processing all data uniformly.
Solution Approach 2:
The system performs preliminary actions by maintaining packet filtering output data in a structured format with rule associations before updated intelligence arrives. This preliminary structuring enables rapid retrieval and selective re-evaluation when updates occur, avoiding the need to reprocess all historical data from scratch.
2Reliability
If comprehensive packet filtering rules are maintained to ensure thorough threat detection, then security coverage is improved, but data volume and system complexity increase
Solution Approach 1:
The system segments the filtering rule set into discrete, identifiable rules with unique identifiers. Each rule can be independently updated, stored, and re-evaluated. This segmentation reduces complexity by making the rule base manageable and allowing selective application of updates to specific rule sets rather than requiring system-wide changes.
Solution Approach 2:
The system implements feedback mechanisms where packet filtering output data is stored with associations to specific filtering rules. This feedback loop allows the system to track which rules generated which output data, enabling efficient re-evaluation when rules are updated and providing visibility into the effectiveness of each rule.
3Measurement precision
If historical packet filtering data is retained for extended periods to enable retroactive threat analysis, then detection capability is improved, but storage requirements and data management burden increase
Solution Approach 1:
The system performs preliminary action by structuring and storing packet filtering output data with explicit associations to filtering rule identifiers during the initial filtering process. This preliminary organization enables efficient retrieval and selective re-evaluation of specific data sets when threat intelligence updates occur, without requiring retention of all possible data combinations.
Solution Approach 2:
The system extracts and retains only the essential elements needed for retroactive analysis - specifically, the association between packet filtering output data and filtering rule identifiers. By extracting only these critical relationships rather than storing complete contextual information, the system enables effective retroactive threat analysis with reduced storage requirements.
Data Source
AI summary
Systems, methods, and apparatuses are described for detection and/or analysis of cyber threats based on updated cyber threat intelligence associated with cyber threats. Packet filtering output data such as logs of packet communications and/or copies of packets may be generated based on first cyber threat intelligence associated with a cyber threat. Updated criteria based on subsequent updated cyber threat intelligence may then be applied to the packet filtering output data.