В работе приведен обзор существующих методов и алгоритмов обнаружения
аномалий с целью структуризации имеющихся данных и последующего отбора …

The evolution of high performance computing technologies has enabled the large-scale
implementation of neuromorphic models and pushed the research in computational …

This paper presents a new weighted local outlier factor method for anomaly detection, which
is underpinned with three novel components:(1) a piecewise linear representation defined …

The detection of seismic activity precursors as part of an alarm system will provide
opportunities for minimization of the social and economic impact caused by earthquakes. It …

Every telecommunication market player is launching innovative business models and
offering better services which in turn have increased the cost of retaining customers …

Inference models such as the confabulation network are particularly useful in anomaly
detection applications because they allow introspection to the decision process. However …

The early detection of cyber threats with cyber-attacks adapted to the nature of information
systems is a crucial cybersecurity problem. This problem and the task of recognizing normal …

This thesis introduces novelty detection techniques that use a combination of Gaussian
processes, extreme value theory and divergence measurement to identify anomalous …

Modern software development often relies on open-source code sharing. Open-source code
reuse, however, allows hackers to access wide developer communities, thereby potentially …

Anomaly detection problems are particularly important in various real-word contest such as
fraud detection, finance, intrusion detection and cyber-security. Several methods that are …