Cybersecurity Risk Modeling via Control Deficit Analysis
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Solution Overview
Problem
Existing risk modeling methods for cybersecurity threats fail to accurately convey the connection between risk values and real-world costs, and do not account for the specific risks and costs of different types of organizations.
Innovation Solution
A novel method for risk modeling that establishes a communicative connection with a database storing threat assessment data mapped to different controls, allowing for the characterization of specific organizations and the computation of risk values based on implemented and baseline control sets.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If a generic risk model is applied to all organizations, then the model can be universally used, but the accuracy of risk assessment for specific organizations deteriorates
Solution Approach 1:
The patent segments the generic risk model into organization-specific models by dividing organizations into different types (e.g., financial, healthcare, manufacturing) based on their characteristics. Each segment receives a tailored risk model that accurately reflects its specific threats, controls, and impact profiles, thereby maintaining universal applicability while improving assessment accuracy for each segment.
Solution Approach 2:
The patent applies local quality by customizing risk model parameters, threat profiles, and control effectiveness factors according to the specific characteristics of each organization type. Instead of using uniform parameters across all organizations, the model adapts local parameters (such as industry-specific threats, organizational size, regulatory environment) to improve measurement precision for each local context.
2Ease of manufacture
If arbitrary numeric values are assigned to risk, then the model is simple to implement, but the connection to real-world cost deteriorates
Solution Approach 1:
The patent transforms the arbitrary numeric risk values into meaningful parameters by introducing a cost function that converts risk scores into estimated monetary losses. This parameter change maintains the simplicity of the underlying risk model while adding a new parameter (estimated cost) that directly connects risk assessments to real-world financial impact, enabling better resource allocation decisions.
3Reliability
If controls are implemented to avoid threats, then the security posture improves, but the organizational cost increases
Solution Approach 1:
The patent implements feedback by using the estimated cost calculations to inform control selection and prioritization. The system provides feedback to organizational leaders showing which controls offer the best security improvement per dollar spent, enabling them to allocate resources efficiently. This feedback loop allows the organization to achieve the necessary security posture while minimizing unnecessary costs by avoiding controls with low cost-effectiveness ratios.
Data Source
AI summary
Risk modeling for cyberspace control deficiencies includes characterizing a subject organization and loading a baseline set of controls, each control mapping to one or more threats to the subject organization. For each of the threats, a baseline risk value is computed from a hypothetical implementation of the baseline set of controls. Concurrently, risk assessment data is uploaded for the subject organization and an implemented set of controls for the organization extracted therefrom. For each of the threats, one or more of the implemented set of controls are mapped thereto and a risk value computed. Thereafter, the baseline risk value compared to the computed risk value producing a risk deficit value. On condition that the risk deficit value exceeds a threshold value, a flag is written in association with the risk assessment data indicating a necessity to modify the implemented set of controls.