Cyber Risk Assessment Using Attack Paths and Vulnerability Context
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Solution Overview
Problem
Existing cyber risk management solutions fail to consider vulnerabilities in the broader context of an organization's operations, business processes, and third-party relationships, are not adaptable to specific organizational needs, and cannot dynamically respond to changing network architectures and adversarial threats.
Innovation Solution
A system and method for determining cyber risk scores by assessing asset weights, generating attack paths, and recommending security controls based on vulnerability impact vectors, allowing for dynamic risk management and adaptation to organizational changes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If standardized cyber risk assessment tools are used, then consistency and ease of operation are improved, but adaptability to specific organizational needs deteriorates
Solution Approach 1:
The system allows organizations to customize risk assessment parameters and weights according to their specific industry, size, and operational context. Each organization can define local quality metrics that reflect their unique risk profile while using the standardized framework, enabling both consistency and adaptability simultaneously
Solution Approach 2:
The risk assessment framework is designed to be dynamic and adaptable, allowing organizations to modify assessment criteria, asset values, and risk parameters as their business environment changes. This dynamic nature enables the standardized tool to adapt to specific organizational needs while maintaining overall framework consistency
2Measurement precision
If isolated vulnerability analysis is performed on individual computing devices, then measurement precision for specific vulnerabilities is improved, but reliability of overall risk assessment deteriorates
Solution Approach 1:
The system merges isolated vulnerability assessments with contextual risk factors including business process impact, asset criticality, and organizational dependencies. By combining precise vulnerability detection with holistic risk context, the system achieves both measurement precision and reliability in overall risk assessment
Solution Approach 2:
The system adds contextual dimensions to traditional vulnerability assessment by incorporating business impact analysis, asset weighting, and risk scenario modeling. This multi-dimensional approach transforms isolated vulnerability data into reliable organizational risk assessments while preserving measurement precision at the vulnerability level
3Ease of operation
If static risk assessment methods are used, then ease of operation is improved, but adaptability to dynamic threats and network changes deteriorates
Solution Approach 1:
The system implements dynamic risk assessment that automatically updates as network topology, assets, and threats change. The framework adapts to new services, features, and security conditions in real-time, maintaining ease of operation through automation while achieving high adaptability to dynamic organizational environments
Solution Approach 2:
The system incorporates continuous feedback loops that monitor network changes, threat intelligence, and risk metric updates. This feedback mechanism enables automatic adaptation to new threats and organizational changes while maintaining operational simplicity through automated adjustments rather than manual reconfiguration
Data Source
AI summary
The present disclosure provides a system and methods for cyber risk management. The system determines risk values for a network environment having one or more assets based on asset weights of the assets and impact vectors of one or more vulnerabilities associated with the assets. The system iteratively generates one or more attack paths using the vulnerabilities, and applies one or more security controls to mitigate the vulnerabilities to prevent attackers from attacking the network environment using any of the attack paths.