# Resilience in the Cyberworld: Definitions, Features and Models
## 5 Discussion
Unspecified disturbances can be triggered by the following causes, for example:  
* Excessive deviation of the physical parameters of the environment from the specified working range. * Too frequent (even not-strong) deviations of the physical parameters of the environment from the specified working range. * Too short a reaction time. * (dynamic) Changes in the specified working or analysis range (e.g., increased operating voltage). * Individualized work or analysis areas. In short, we define resilience for CPS (oS) as follows:  
_\"A CPS (oS) is resilient if it has the ability to react to specified and unspecified disturbances in a way that preserves its function and reacts quickly. This reaction includes the early detection, minimization, prediction or even avoidance of disturbances. In addition it needs to have the capability to anticipate future challenges and to prepare itself for those\"_. According to our definition, we discuss in the following four different types of systems, i.e., primitive system without error handling (1), fault-tolerant system (2), resilient system (3) and total-resilient system (4) shown in Figure 7.  
Figure 7: Schematic representation of four different systems: (**a**) primitive system without error handling, (**b**) fault-tolerant system, (**c**) resilient system, (**d**) optimal system. A system such as the one shown in Figure 7a without any form of error detection, should not be in use today, especially not in the area of critical infrastructure. This system is not able to deal with a fault, understand it or resist its negative effects. As an example, a memory without error correction can be mentioned here. Figure 7b shows a fault-tolerant system. These systems are currently the ones most commonly used. If this system detects an error, this error can often be corrected. If the error cannot be corrected, the user is informed. If an error is not detected, e.g., because it has no direct effect on the functionality of the system, it is a corrupt system that can, among other things, supply incorrect data. As an example, a memory with error correction can be mentioned here. Figure 7c shows our idea of a resilient system. This idea of a resilient system was developed using our model of key actions. The probability that an error was not detected (corrupt system) or that an error was detected but cannot be handled (inform users) is given but should be very low. As an example, a network with adaptive routing can be mentioned here. Figure 7d shows an optimal system, i.e., a system that can cope with all adverse circumstances. Such a system acts autonomously, learns independently, solves complex tasks, can react to unforeseen events and does not require any additional maintenance or action by a human. Such an optimal system cannot exist comprehensively within the current state of the art. It is in our view, the ultimate target system when designing resilient systems. In the current development process for highly reliable systems in critical infrastructure, it makes sense to develop increasingly resilient systems and to make fault-tolerant systems resilient. However, resilience is an extremely dynamic concept, as the many different definitions show. Ultimately, however, resilience is not only the ability to deal with errors, but also the realization that errors will definitely happen. It is irrelevant whether these errors are symptoms of a malicious attack, environmental influences or wear and tear. In order to effectively implement resilience, a holistic understanding of the system design and the threat situation is necessary. Additionally, such a system architecture must offer possibilities for expansion (during normal operation), since resilience is subject to constant change due to its dynamics.