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 …

Over the last five years there has been an increase in the frequency and diversity of network
attacks. This holds true, as more and more organizations admit compromises on a daily …

Network intrusion detection is the process of identifying malicious activity in a network by
analyzing the network traffic behavior. Data mining techniques are widely used in Intrusion …

Network traffic monitoring and analysis-related research has struggled to scale for massive
amounts of data in real time. Some of the vertical scaling solutions provide good …

The emergence of ground-breaking technologies such as artificial intelligence, cloud
computing, big data powered by the Internet, and its highly valued real-world applications …

Anomaly detection (AD) use within the network intrusion detection field of research, or
network intrusion AD (NIAD), is dependent on the proper use of similarity and distance …

Intrusion Detection Systems (IDSs) are one of the key components for securing computing
infrastructures. Their objective is to protect against attempts to violate defense mechanisms …

With an exponential increase in the usage of different types of services and applications in
cloud computing environment, the identification of malicious behavior of different nodes …

With exponential growth in the number of computer applications and the sizes of networks,
the potential damage that can be caused by attacks launched over the Internet keeps …

Modern network intrusion detection systems must be able to handle large and fast changing
data, often also taking into account real-time requirements. Ensemble-based data mining …