Rule System Adaptation for Network Change Detection
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing computing systems face challenges in maintaining accurate and relevant rule systems for data analytics due to changes in computing systems within a network, such as updates to hardware, software, or firmware, which can lead to variations in log content and event interpretation.
Innovation Solution
A method is introduced to modify a rule system by receiving an indication of changes to computing systems within a network, establishing whether the rule system is affected, and automatically updating or creating new rules to account for these changes, using an information flow that includes knowledge about new events and event changes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If the rule system is manually maintained and updated, then the accuracy of data analytics can be preserved, but the time and resources required for maintenance increase significantly
Solution Approach 1:
The rule system automatically detects changes in computing systems within the network and self-updates its rules without requiring manual intervention. The system monitors event data, identifies changes in computing system configurations or behaviors, and automatically modifies the rule set to adapt to these changes, thereby maintaining analytics accuracy while eliminating manual maintenance time.
Solution Approach 2:
The system implements a feedback mechanism where event data from computing systems is continuously analyzed to detect changes. This feedback loop triggers automatic rule modifications when changes are detected, ensuring the rule system remains synchronized with the current state of computing systems without requiring manual updates.
2Adaptability or versatility
If the rule system is automatically updated to adapt to changes, then the relevance of data analytics is maintained, but the complexity of the system increases
Solution Approach 1:
The rule system is segmented into modular components: event data collectors, change detectors, rule generators, and rule repositories. Each component performs a specific function independently, making the overall system easier to manage and understand despite its automatic adaptation capabilities. The segmentation allows complex adaptation logic to be distributed across multiple simple, focused modules.
3Stability of the object's composition
If manual updates to the rule system are performed, then system stability is maintained, but the responsiveness to changes in computing systems decreases
Solution Approach 1:
The system performs preliminary actions by continuously monitoring event data and detecting changes in computing systems before these changes impact analytics accuracy. By proactively identifying changes and automatically updating rules in advance, the system maintains stability while being highly responsive to emerging changes in the computing environment.
Data Source
AI summary
In an example, a method is described. The method comprises receiving an indication of a change to a computing system useable in a computing network. The method further comprises establishing whether a rule system is affected by the change. In response to establishing that the rule system is affected by the change, the method causes the rule system to be modified to account for the change.