# Resilience and Resilient Systems of Artificial Intelligence: Taxonomy, Models and Methods
## 3 Background, Taxonomy and Ontology  
### The Concept of System Resilience  
The concept of resilience has become widespread in systems engineering and the respective property is actively studied in technical systems. Resilience in this context expands the concept of dependability of technical systems, emphasizing the need to create systems that are flexible and adaptive [15]. Cybersecurity experts define resilience as the ability to anticipate, withstand, recover from, and adapt to adverse conditions, external influences, attacks, or system disruptions [16]. Since 2005, many definitions of system resilience have been proposed. In [17], the resilience of a system was formulated as its ability to maintain its functions and structure in the face of internal and external changes and to degrade in a controlled manner when necessary. In [18], resilience is defined as the ability of a system to withstand significant disturbances within acceptable degradation parameters and to recover within an acceptable time with balanced costs and risks. In [19], the authors consider the property of system resilience to the disturbing event(s) as the ability of the system to effectively reduce the magnitude and duration of deviations from the target levels of system performance under the influence of this event(s). Other researchers [20] formulate resilience as the ability of a system to maintain functionality and recover from losses caused by extreme events. In [21], the resilience of a system is understood as the internal ability of the system to adjust its functioning before, during and after changes or disturbances, or during changes or disturbances to maintain the necessary operations in both expected and unexpected conditions. In a more recent work [22], resilience is understood as the ability of a constructed system to autonomously perceive and respond to adverse changes in the functional state, withstand failure events and recover from the consequences of these unpredictable events. Some researchers [23] define resilience in a shorter way: the ability of the system to withstand stressors. In [24], resilience was defined as the ability of a system to adapt to changing conditions, withstand disturbances and recover from them. Therefore, there is a need to ensure the resilience of AI-algorithms, given their ability to continue to function under varying system requirements, thus changing the parameters of the physical and information environment, as well as the emergence of unspecified failures and malfunctions. The stages of disturbance processing by the resilient system are best described in the report of the US National Academy of Sciences in 2012 on the example of resilience to natural disasters. Four main stages were highlighted (Figure 1) [25]:  
- planning and preparation of the system;  
- absorption of disturbance;  
- system recovery;  
- system adaptation. Figure 1: Stages of resilience. At the stage of planning and preparation for destructive disturbances, a resilient system can perform the following actions:  
* risk assessment through system analysis and simulation of destructive disturbances;
* implementation of methods for detecting destructive disturbances;
* elimination of known vulnerabilities and implementation of a set of defense methods against destructive disturbances;
* ensuring appropriate backup and recovery strategies. The absorption stage is designed to implement unpredictable changes in the basic architecture or behavior of the system, depending on what exactly is subject to destructive influence. Absorption mechanisms can have a multi-layered structure, implementing protection in depth, when the system determines which mechanism should be used if the threat cannot be absorbed at this level. If it is impossible to avoid degradation, then the mechanism of controlled degradation (graceful degradation) is implemented, when the core operations of the system take priority over non-essential services for as long as possible.