Cyber Risk Taxonomy for Multi-Entity Asset Footprint Prioritization
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Solution Overview
Problem
Existing systems struggle to efficiently identify and manage cyber security risks across a large number of client networks and target entities, particularly for managed security service providers (MSSPs), due to the complexity and resource-intensiveness of identifying and distinguishing cyber assets, monitoring for vulnerabilities, and determining the urgency of remediation actions.
Innovation Solution
A system and method for identifying cyber asset footprints, organizing cyber security risk information using a risk factor taxonomy, and generating alerts and reports based on correlations between cyber asset footprints and risk factors, enabling automated remediation actions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual identification and monitoring of cyber security risks is performed, then accuracy of risk assessment is improved, but time consumption and resource requirements increase significantly
Solution Approach 1:
The system enables self-service through automated risk identification and assessment. The computer system automatically identifies cyber asset footprints, monitors for vulnerabilities, and assesses risks without requiring manual intervention, thereby maintaining high accuracy while significantly reducing time consumption and resource requirements.
Solution Approach 2:
The patent replaces manual mechanical processes with automated computer-based systems. The computer system performs automated identification of cyber assets, monitoring of vulnerabilities, and risk assessment, substituting human manual operations with automated electronic processes that achieve both accuracy and efficiency.
2Quantity of substance
If comprehensive monitoring of multiple data sources is implemented, then completeness of risk information is improved, but system complexity increases
Solution Approach 1:
The system segments the complex monitoring task into distinct functional modules: cyber asset footprint identification, vulnerability monitoring, and risk assessment. Each module handles specific aspects of risk information, making the overall system more manageable while maintaining comprehensive coverage through organized categorization of risk factors.
Solution Approach 2:
The computer system performs multiple functions within a unified platform, including identification of cyber assets, monitoring of vulnerabilities across multiple data sources, assessment of risks, and generation of remediation actions. This multi-functionality consolidates what would otherwise require separate systems into one integrated solution.
3Speed
If automated remediation actions are implemented, then response time to security threats is improved, but accuracy of risk prioritization becomes more critical
Solution Approach 1:
The system incorporates feedback mechanisms where risk assessments and prioritizations are continuously refined based on monitored data. The computer system monitors for vulnerabilities, assesses risks, and generates remediation actions, then tracks the effectiveness of these actions, using this feedback to improve the accuracy of future risk prioritizations while maintaining rapid response times.
Data Source
AI summary
A method for managing cyber security risk for a client entity communicating with a plurality of target entities is disclosed. In one aspect, the method includes identifying a plurality of cyber asset footprints, wherein each cyber asset footprint comprises cyber assets associated with a different one of the target entities. In another aspect, the method includes monitoring a plurality of data sources comprising cyber security risk information to generate source data, wherein the source data is organized based on a plurality of risk factors, and wherein the risk factors are classified according to a cyber security risk taxonomy. In yet another aspect, the method includes identifying relevant observations in the source data, wherein each relevant observation comprises information related to one the risk factors, and wherein each relevant observation is identified based on a correlation between the information related to the risk factor and one of the cyber asset footprints.