## 3 CPS Resilience Quantitative Assessment Framework
### Step 4: Resilience curve display
#### 3.4.3 Comparison with Existing Frameworks  
To contextualize the advantages of the proposed framework, it is important to compare it with existing cyber resilience assessment approaches. While numerous frameworks have been developed in recent years, most fall into one of the four categories discussed in Section 2: static assessment metrics, dynamic performance modeling, cyber domain security modeling, and red-teaming or adversarial simulations. Each offers valuable perspectives but also presents limitations when applied to complex, multi-domain CPS environments. This section provides a comparative analysis between our framework and representative methods from each category, focusing on key features.  
As summarized in Table 2, the comparison covers six key evaluation dimensions: integrity, availability, performance curve generation, cyber-physical coupling, feedback support for design, and modeling scalability. Each method is assessed based on whether it fully supports (), partially supports (), or does not support () the corresponding dimension. These dimensions are chosen to reflect the core capabilities required for CPS resilience assessment frameworks, encompassing both cyber and physical layers, dynamic performance representation, and the framework's ability to support iterative design improvement and generalizability across use cases.  
The results indicate that while static assessment metrics and red-teaming simulations are effective for evaluating cyber-layer attributes such as integrity and availability, they lack dynamic performance modeling and cyber-physical integration capabilities. Similarly,  
\begin{table}
\begin{tabular}{c c c c c c} \hline \hline
**Evaluation** & **Static** & **Red-Teaming** & **Dynamic** & **Cyber-Layer** & **Proposed** \\
**Dimension** & **Assessment** & **and Adversarial** & **Performance** & **Security** & **Framework** \\  & **Metrics** & **Simulation** & **Modeling** & **Modeling** & **Framework** \\ \hline Integrity & ✓ & & & & \\ Availability & & ✓ & & & \\ Performance & & & & \\ Curve & & & & \\ Cyber-Physical & & & & & \\ Coupling & & & & & \\ Feedback for & & & & & \\ Design & & & & & \\ Modeling & & & & & \\ Scalability & & & & & \\ \hline \hline \end{tabular}
\end{table}
Table 2: Comparison between the proposed resilience assessment framework and representative existing methods across key evaluation dimensions, where indicates full support, indicates partial support, and indicates limited support.  
existing dynamic modeling approaches often capture time-dependent behavior but remain limited to specific domains or lack feedback mechanisms for system-level design optimization. The proposed framework addresses these limitations by integrating stochastic modeling of cyber-layer disruptions with physical-layer performance dynamics, thereby enabling end-to-end resilience evaluation. In addition, the framework supports design feedback and allows for flexible parameterization to improve modeling scalability across diverse application scenarios. This comparative analysis demonstrates the comprehensive nature and practical utility of the proposed approach in advancing CPS resilience engineering.