Vendor-Agnostic Cyber Defense Framework for Detection Gap Analysis
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Organizations lack a comprehensive understanding of the relationships between their cyber-related telemetry detections and tools, leading to incomplete threat modeling and ineffective cyber defense strategies, as well as a failure to respond to cyber threats in real time due to proprietary detection logic maintained by cyber defense vendors.
Innovation Solution
A vendor-agnostic software-defined meta-framework operationalizes adversarial technique frameworks to automate cyber defense decisions, using a defense decision system that processes and analyzes telemetry data to identify detection gaps and update coverage in real time, enabling informed decision-making and rapid response.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If cyber defense vendors keep proprietary detection logic hidden to maintain competitive edge, then vendor competitiveness is improved, but organization's understanding of detection coverage and threat posture deteriorates
Solution Approach 1:
The patent introduces an intermediary framework that maps vendor-specific detection logic to standardized adversarial technique frameworks (ATT&CK, Cyber Kill Chain). This intermediary layer allows organizations to understand detection coverage without requiring vendors to disclose proprietary logic, resolving the contradiction by enabling information transparency through standardization while preserving vendor competitive advantages.
Solution Approach 2:
The system transforms vendor-specific detection parameters into standardized framework parameters. By changing the parameter space from proprietary vendor metrics to universal adversarial technique coverage metrics, organizations gain comparable understanding of detection capabilities across different vendors without exposing proprietary detection logic.
2Ease of operation
If organizations rely on vendor proprietary detection logic, then implementation simplicity is improved, but accurate threat modeling and informed decision-making deteriorate
Solution Approach 1:
The patent creates a universal mapping framework that works across multiple vendor platforms and detection systems. This single framework serves multiple functions: it maintains implementation simplicity by providing a unified interface while simultaneously improving threat model accuracy by enabling comprehensive coverage analysis against standardized adversarial techniques.
3Measurement precision
If comprehensive detection coverage analysis is performed across all adversarial techniques, then threat posture understanding is improved, but system complexity and resource requirements worsen
Solution Approach 1:
The patent segments the comprehensive adversarial technique framework into manageable subsets and categories. By dividing the large-scale analysis into smaller, organized segments (different tactics, techniques, and procedures), the system achieves thorough threat posture understanding while maintaining manageable complexity through structured organization and phased analysis.
4Speed
If real-time detection coverage updates are implemented, then response speed to cyber threats is improved, but computational resource consumption worsens
Solution Approach 1:
The patent implements feedback mechanisms that monitor detection coverage and trigger updates only when changes are detected. This feedback-driven approach enables real-time response capability while conserving computational resources by avoiding continuous unnecessary processing, updating the threat model only when actual changes in detection coverage or adversarial techniques occur.
Data Source
AI summary
In some embodiments, a method can include identifying detection coverage of a set of adversarial techniques based on telemetry data and a detection instance of an environment. The method can further include determining a subset of detection coverage that has a metric value below a metric value threshold and among the detection coverage for the set of adversarial techniques. The method may further include identifying at least one detection instance associated with the subset of detection coverage. The method can further include presenting, via a graphical user interface, a representation of at least one of the subset of detection coverage or the at least one detection instance associated with the subset of detection coverage. The method can further include updating the subset of detection coverage based on the telemetry data, the detection instance, or the at least one detection instance to improve the metric value.


