Cyberspace Operations Modeling for Probabilistic Attack Paths
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Solution Overview
Problem
Traditional methods for estimating the likelihood of success and probable effects of cyberoperations rely on intuitive understandings of target networks, lacking a repeatable model that consistently outputs the same outcome, and fail to account for uncertainties and network configurations.
Innovation Solution
A system and method for modeling cyberspace operations using an operational environment model, integrating network scan data to determine attack paths based on probabilities and uncertainties, incorporating functional modeling techniques to assess the impact of attacks on network elements.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional intuitive methods are used to estimate cyberoperation success, then the process is simple and quick, but the results lack repeatability and consistency
Solution Approach 1:
The system segments the cyberoperation modeling into distinct components: operational environment model (network elements, configurations, vulnerabilities), capability models (adversary actions), and probabilistic calculation modules. This segmentation allows each component to be independently defined and reused, improving repeatability while managing complexity through modular architecture.
Solution Approach 2:
The system transforms qualitative intuitive assessments into quantitative probabilistic parameters. By assigning numerical probabilities to network element configurations, vulnerability states, and capability effectiveness, the system enables consistent, repeatable calculations that can be systematically analyzed and compared across different scenarios.
2Measurement precision
If detailed network configurations and uncertainties are accounted for, then the accuracy of success prediction improves, but the computational complexity increases
Solution Approach 1:
The system calculates probabilities for network elements based on their relevance to the specific cyberoperation being analyzed. Rather than exhaustively modeling every possible network element state, the system focuses computational resources on elements and configurations that have significant impact on operation success, achieving accurate predictions without unnecessary computational overhead.
Solution Approach 2:
The system uses operational environment models that can be copied and reused for different cyberoperation scenarios. Once a network model is created with its configurations, vulnerabilities, and interconnections, it can be replicated and applied to analyze multiple different adversary capabilities and attack scenarios, improving measurement precision across analyses while avoiding redundant modeling work.
3Adaptability or versatility
If multiple possible configurations of network elements are considered, then the completeness of the model improves, but the time required for analysis increases
Solution Approach 1:
The system performs preliminary probabilistic calculations to determine which network element configurations are most likely to be present in the target environment. By pre-calculating configuration probabilities and prioritizing the most likely scenarios, the system achieves comprehensive modeling of multiple configurations while significantly reducing the time required to analyze less probable alternatives.
Solution Approach 2:
The system dynamically adjusts the level of detail modeled based on the specific cyberoperation being analyzed and the available time resources. For time-critical operations, the system may focus on the most probable configurations, while for strategic planning with more time available, it can explore a broader range of possible configurations, achieving adaptability between completeness and analysis time.
Data Source
AI summary
A method, system, and computer-readable media for modeling cyberspace operations and the effects thereof. Network and connectivity data for an operational environment model may be retrieved from a network scan. Likelihood data that a network element takes a plurality of possible configurations may be mapped. Determination of a probability of effect of a capability acting on the network element may be based on the likelihood data and uncertainties associated with the capability. Multiple attacks within the operational environment model may be modeled to determine an attack path therethrough. Functional modeling techniques to model functional impacts of attacks on an operational environment model are also disclosed.