## 4 Results
### General Synthesis of Results
\begin{table}
\begin{tabular}{l l} \hline \hline
**CI Sector** & **Ref.** \\ \hline Transportation systems sector & [22; 68; 101; 102; 103; 104; 105; 106; 107] \\ \hline Energy sector & [114; 115; 116; 117; 118; 119; 120] \\ \hline Healthcare and public health sector & [108; 109; 110] \\ \hline IT sector & [111; 112; 113] \\ \hline Emergency services sector & [121] \\ \hline Communication sector & [99] \\ \hline Not categorized & [9; 20; 122; 123; 124; 124; 125; 126; 127; 128; 129; 130; 131; 132; 133; 134] \\ \hline \hline \end{tabular}
\end{table} 
Table 5: CI sectors addressed by the considered papers. Figure 2: Number of yearly publications categorized by source type. cybersecurity and threat analysis and modeling in the literature. Additionally, the network visualization in Figure 4 represents the relationship between articles and shared keywords. Each article is connected to the keywords it uses, showing how different articles overlap based on common topics. The most central keywords in this network are National Institute Standards and Technology (NIST), framework, goals, and anticipation. This figure shows that articles related to \"cyber resilience\" and \"NIST\" are likely discussing frameworks or standards for assessing and improving resilience in cybersecurity. In Figure 4, the concepts of physical security, cybersecurity, risk, and IoT are all interlinked through the paper Qi4 [128]. As interpreted from the figure, IoT acts as a key enabler in merging physical infrastructure with digital systems, hence opening the door for real-time data collection, analytics, and reactive measures in risk assessment frameworks. The interplay between these components highlights the increasing importance of IoT as a key point to be considered for integrated risk management in cyber-physical systems (CPSs) [135]. This implies that future studies could focus on understanding and extending the role of IoT in the risk management related to CPSs, specifically in addressing cyber-physical vulnerabilities. However, a limitation can be noticed in Figure 4. The model depicted in the figure shows a lack of social aspect considerations. As per the new complex system definition [136], the social part includes human behaviors, organizational dynamics, and societal impacts. Cyber-physical social systems (CPSSs) include social aspects interacting with cyber and physical elements, thus creating interdependencies and potentially introducing new types of risks. Although digital technologies, such as digital twin, have been proposed as solutions to enhance resilience in CPSSs [30], the vulnerabilities and corresponding solutions of CPSSs are not widely studied. A separate network of frequently used keywords is shown in Figure 4; it revolves around the paper Qi1 [129]. It involves resilience features such as recovery, resistance, anticipation, and adaptation. These features are interlinked within the same network, alongside the 'NIST' standard, illustrating the importance of aligning resilience attributes with established regulatory frameworks and best practices. Finally, as shown in Figure 4, cutting-edge technologies such as digital twin and blockchain are in the same network as the keywords \"critical performance indicators\" and \"critical success factors\", where the study Qs59 [117] is located. This relationship further signifies the need to create quantitative metrics for resilience attributes. Figure 3: Most frequently occurring keywords across the articles reviewed. The keywords that are used in the search query like resilience and cyber are not considered.