# Resilience and Resilient Systems of Artificial Intelligence: Taxonomy, Models and Methods
## 3 Background, Taxonomy and Ontology
### Vulnerabilities and Threats of AISs
Prior-probability shift is another type of drift and is associated with the appearance of data  
Figure 3: Visual illustration of different types of concept drift for three-class classifier: (a)—original data distribution and decision boundary of classifier; (b)—real concept drift; (c)—virtual concept drift; (d)—imbalance of classes; (e)—the emergence of a new class; (f)—class merging. imbalance or a change in the set of concepts or contexts. In the case of data classification, prior-probability shift means that there is a change in probabilities \(\mathrm{P}(\mathrm{y})\) due to unbalanced class samples (Figure 3d), emergence of novel classes (Figure 3e), removal of existing classes (Concept deletion), concept fusion (Figure 3f) or splitting certain classes into several subclasses (Concept splitting). In terms of the time characteristics of concept drift, they can be classified into abrupt (sudden), gradual, incremental, re-occurring and blip [36]. Abrupt concept drift is the rapid change of an old concept to a new one. In this case, the performance of the model suddenly decreases, and there is a need to quickly train a new concept to restore performance. Gradual drift has an overlapping concept, and after some period of time, the new concept becomes stable. In incremental concept drift, certain concept vanished from the observations at certain time and never occurred again. In a recurring type of drift, a concept reappears after a long period of time. A recurring change of concept occurs in the flow. Such drift can have cyclic and acyclic behavior. Cyclical drift occurs when there are seasonal fluctuations. For example, sales of cold clothes increase during the summer season. An acyclic phenomenon is observed when the price of electricity increases due to an increase in the price of gasoline and normally it returns to the previous price. A blip drift is a very rapid change in a concept or a rare event, so it is considered as an outlier in a stationary distribution. In other words, in general, blip drift is usually not even considered to be concept drift. Significant destructive effects on AIS can be caused by various faults. Faults in a computer system can cause errors. An error is such manifestations of faults that leads to a deviation of the actual state of a system element from the expected one [34]. If a fault does not cause an error, then such a fault is called a sleeping fault. As a result of errors, failures can occur, meaning that the system is unable to perform its intended functionality or behavior. In general, faults can be divided into four groups:  
* physical faults that lead to persistent failures or short-term failures of AIS hardware;
* design faults, which are the result of erroneous actions made during the creation of AIS and lead to the appearance of defects in both hardware and software;
* interaction faults that result from the impact of external factors on AIS hardware and software;
* software faults caused by the effect of software aging, which lead to persistent failures or short-term failure of AIS software. Failures of the system and its components can be caused by a single fault, a group of faults, or a sequential manifestation of faults in the form of a \"pathological\" chain. Figure 4 illustrates the causal relationship between a hardware fault, error, and failure [37]. A failure causes a violation of the predictable behavior of a neural network that is deployed to perform its task in a computing environment. Hardware faults can be classified according to their time characteristics (Figure 5) [37]:  
* permanent fault which is continuous and stable over time as result of physical damage;
* transient fault which can only persist for a short period of time as result of external disturbances. Figure 4: Propagation of hardware failure from the physical layer of the computing environment to the behavioral layer of the neural network application.