Model-Based Cyber Vulnerability Assessment System
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Solution Overview
Problem
Traditional cyber vulnerability assessments (CVAs) are manually performed, which is time-consuming and inefficient in identifying and mitigating vulnerabilities across multiple levels of a computer system or network.
Innovation Solution
A model-based CVA system that automatically generates cyber vulnerability attack surface models by collecting data at network, platform, and binary levels, analyzing relationships between components, and constructing a hierarchical model representing the attack surface.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual cyber vulnerability assessment is performed, then comprehensive vulnerability identification can be achieved, but the process is time-consuming and inefficient
Solution Approach 1:
The patent creates a virtual copy of the target system through automated data collection at multiple levels (network, platform, binary). This virtual model replicates the actual system state, allowing comprehensive vulnerability assessment without manual inspection of every system component, thus reducing time while maintaining assessment completeness
Solution Approach 2:
The system performs preliminary automated data collection and model generation before the actual vulnerability assessment. By pre-building the virtual model and pre-processing data from multiple sources, the patent enables rapid vulnerability identification without requiring manual analysis of all system components from scratch
2Productivity
If automated model-based CVA is implemented, then assessment efficiency is improved, but system complexity increases
Solution Approach 1:
The patent segments the complex vulnerability assessment system into distinct functional modules: data collection modules (network, platform, binary levels), a correlation engine, and a model generator. This segmentation allows each component to handle specific tasks independently, making the overall complex system more manageable and easier to implement while maintaining high efficiency
Solution Approach 2:
The virtual model acts as an intermediary between the complex real system and the assessment process. Instead of directly analyzing the complex actual system, the patent creates a simplified virtual representation that captures essential characteristics, allowing efficient vulnerability assessment without directly manipulating the complex original system
3Reliability
If multi-level data collection is performed, then comprehensive vulnerability coverage is achieved, but data processing complexity increases
Solution Approach 1:
The patent merges data from multiple collection levels (network, platform, binary) into a single unified virtual model. The correlation engine integrates these diverse data sources, combining their insights to achieve comprehensive vulnerability coverage while managing processing complexity through systematic integration rather than separate analysis of each data level
Data Source
AI summary
A system includes one or more processors configured to collect data at multiple levels from a target environment via one or more cyber vulnerability (C V) data collection modules, the multiple levels comprising a network level, a platform level, and a binary level. The one or more processors are further configured to analyze the collected data, via a correlation engine, to identify relationships between entities in the collected data across the multiple levels, and to derive one or more blocks representative of the entities. The one or more processors are additionally configured to create one or more links between the one or more blocks based on the identified relationships, and to construct, via a model generator, a CV attack surface model comprising the one or more blocks connected via the one or more links.