Anomaly detection has been used for decades to identify and extract anomalous
components from data. Many techniques have been used to detect anomalies. One of the …

The increasing number of security attacks have inspired researchers to employ various
classifiers, such as support vector machines (SVMs), to deal with them in Intrusion detection …

Security is one of the main requirements of the current computer systems, and recently it
gains much importance as the number and severity of malicious attacks increase …

The Internet connects hundreds of millions of computers across the world running on
multiple hardware and software platforms providing communication and commercial …

Automatic network intrusion detection has been an important research topic for the last
20years. In that time, approaches based on signatures describing intrusive behavior have …

The detection of illicit nuclear materials is a major tool in preventing and deterring nuclear
terrorism. The detection task is extremely difficult because of physical limitations of nuclear …

Data readings from wireless sensor networks (WSNs) may be abnormal due to detection of
unusual phenomena, limited battery power, sensor malfunction, or noise from the …

Anomaly detection is an observation of irregular, uncommon events that leads to a deviation
from the expected behaviour of a larger dataset. When data is multiplied exponentially, it …

Anomaly detection is a challenging problem that has been researched within a variety of
application domains. In network intrusion detection, anomaly based techniques are …

Detection of intrusion in network is necessary since the intrusion may create harm or attack
any application which needs to be detected and prevented. Although there are various …