While many advances towards effective anomaly detection techniques targeting specific applications have been made in recent years, little work has been done to develop application-agnostic approaches to the subject.#R##N##R##N#In this article, we present such an approach, in which anomaly detection methods are treated as formal, structured objects.#R##N##R##N#We consider a general class of methods, with an emphasis on methods that utilize structural properties of the data they operate on.#R##N##R##N#For this class of methods, we develop a decomposition into sub-methodsâsimple, restricted objects, which may be reasoned about independently and combined to form methods.#R##N##R##N#As we show, this formalism enables the construction of software that facilitates formulating, implementing, evaluating, as well as algorithmically finding and calibrating anomaly detection methods.
['André Eriksson', 'Hedvig Kjellström']
A Formal Approach to Anomaly Detection