**2.4 Dynamic checklists of resilience issues and indicators**

One of the ways to use resilience issues and indicators practically [21], is to put them into "lists" (checklist) and in the concept it is done in a dynamic way, allowing to dynamically create checklist appropriate for a given case using available indicators or adding new ones to the list. In order to make the creation/drafting of these dynamic checklists (DCLs) easier and allow for comparison and benchmarking of results, the user is encouraged to use the list suggested by the concept, namely (**Figure 6**):


• Downtime [h]

• Recovery time [h]

• Recovery rate [%]

• Disruption time [h]

• Loss of functionality [% over h]

*DOI: http://dx.doi.org/10.5772/intechopen.97810*

• Improvement/adaptation/transformation [%]

*Resilience and Situational Awareness in Critical Infrastructure Protection…*

functionality, duration or a combination of these, etc.).

It should be noted that these are the RESULTING macro-indicators, and not the INPUT indicators as the resilience indicators and functional indicators mentioned above. These macro-indicators can also be used for "stress-testing", in which case these can be compared with the critical thresholds (e.g. for the maximum loss of

**Robustness** characterizes the absorbing capacity of the smart critical infrastructure [23]. NL uses robustness as defined by the National Infrastructure Advisory Council (NIAC) [24], i.e. "the ability to maintain critical operations and functions in the face of crisis" [25]. It can be seen as the protection and preparation of a system facing a specific danger. The objective of the robustness component is to identify measures that can help the system withstand or adapt to a hazard. It emphasizes the ability of an infrastructure to withstand the incident if the protective measures fail. It also integrates the capacity of the infrastructure to function in a degraded state. The importance of robustness is not necessarily defined by how the infrastructure continues to function in the face of an incident but rather by how it is able to continue to accomplish its mission and to provide its products and services through preventative measures, mitigation, or absorption capabilities [25]. Robustness is defined as the capacity of the smart critical infrastructure to endure the effects of a negative event and thereby absorb its impact. As shown in

**Figure 4**, it is measured as the ratio of the percentage of the lowest FL after the disruption, i.e. at time t2, to the FL during normal operation, i.e. at time t0.

Robustness <sup>¼</sup> *FLt*<sup>2</sup>

structure absorbs a disruptive event while the smart critical infrastructure undergoes a decrease in its functionality level. As illustrated in **Figure 4**, it is

lost in a given threat situation. It is measured by the area of the curve

Loss of functionality ¼

measured as the difference between t2 and t1.

time [26, 27], e.g. losing 10% in 10 hours.

**69**

*FLt*<sup>0</sup>

**Absorption time** is defined as the time during which the smart critical infra-

**Loss of functionality** is the functionality of the smart critical infrastructure

(an approximation) between the time when the smart critical infrastructure starts to lose its functionality (t1) to the time when it reaches the initial state (t4) (see **Figure 4**). The approximation is done for the area above the curve to a well-defined shape, e.g. a triangle. The output would be the percentage loss of functionality in

> ð*t*4 *t*1

� 100% (1)

½ � *FLt*<sup>1</sup> � *FL t*ð Þ *dt* (3)

Absorption time ¼ *t*<sup>2</sup> � *t*<sup>1</sup> (2)

**Figure 6.** *Hierarchical structure of the checklist in the concept.*
