CRApr 25

Core Logic and Algorithmic Performance Enhancements for a System Vulnerability Analysis Technique for Complex Mission Critical Systems Implementation

arXiv:2604.2317031.1
Predicted impact top 62% in CR · last 90 daysOriginality Synthesis-oriented
AI Analysis

Incremental improvement to a domain-specific vulnerability analysis tool for mission-critical systems.

The authors replaced Boolean-only logic with generic .NET types in the SONARR vulnerability analysis tool, enabling calculations with diverse data types, and added multi-compute capabilities. Performance tests showed expanded processing capability for larger workloads.

Core logic and processing improvements were made to the software for operations and network attack results review (SONARR) and are presented, herein. Previous SONARR versions' Boolean-only logic, derived from the Blackboard Architecture, was replaced with generic logic that allows any .NET type (e.g., integers, decimals, strings) to be utilized within facts. This allows calculations and equality operations with all data types to drive the algorithm's processing of network models. Additionally, multi-compute capabilities were implemented to increase the processing power for larger workloads. In this paper, the new logic objects are described, examples are presented to illustrate the efficacy of creating digital-twin systems using the new generic logic, and performance test results are presented that illustrate the expanded processing capability from the multi-compute functionality.

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