In supervised learning‐based classification, ensembles have been successfully employed to
different application domains. In the literature, many researchers have proposed different …

Cyber security threats have been growing significantly in both volume and sophistication
over the past decade. This poses great challenges to malware detection without …

Automation in anomaly detection, which deals with detecting of unknown attacks in the
network traffic, has been the focus of research by using data mining techniques in recent …

Intrusion detection system, IDS, traditionally inspects the payload information of packets.
This approach is not valid in encrypted traffic as the payload information is not available …

Traditional cybersecurity architectures incorporate security mechanisms that provide
services such as confidentiality, authenticity, integrity, access control, and non-repudiation …

The rate of data generation is enormously growing due to the number of internet users and
its speed. This increases the possibility of intrusions causing serious financial damage …

We consider the systems of detection and prevention of intrusions in modern
telecommunication systems and networks. Methods of monitoring events, consisting of …

Sensing of human motion is very important for human-computer interactive applications
such as virtual reality, gesture recognition, and communication. A vision system is suitable …

In this thesis, we present the risks posed by Advanced Persitent Threats (APTs) and propose
a two-step approach for recognising when detected attacks are part of one. This is part of the …

Summary Intrusion Detection System is one of the important security mechanisms in today's
information era. Two different approaches are used for intrusion detection: signature based …