Anomaly detection is crucial in various applications, particularly cybersecurity and network
intrusion. However, a common challenge across anomaly detection techniques is the …

In light of the escalating ubiquity of the Internet, the proliferation of cyber-attacks, coupled
with their intricate and surreptitious nature, has significantly imperiled network security …

Machine learning (ML) has become an important paradigm for cyberthreat detection (CTD)
in the recent years. A substantial research effort has been invested in the development of …

Connected and Autonomous Vehicles (CAVs) enable various capabilities and functionalities
like automated driving assistance, navigation and path planning, cruise control, independent …

Despite the benefits of the Internet of Things (IoT), the growing influx of IoT-specific malware
coordinating large-scale cyberattacks via infected IoT devices has created a substantial …

Abstract Machine Learning techniques for network-based intrusion detection are widely
adopted in the scientific literature. Besides being highly variable, network traffic behavior …

As a security defense technique to protect networks from attacks, a network intrusion
detection model plays a crucial role in the security of computer systems and networks …

Recently proposed methods in intrusion detection are iterating on machine learning
methods as a potential solution. These novel methods are validated on one or more …

Cybersecurity has become one of the focuses of organisations. The number of cyberattacks
keeps increasing as Internet usage continues to grow. An intrusion detection system (IDS) is …

The Internet of Things (IoT) has redefined several aspects of our daily lives, including
automation and control of the living environment, innovative healthcare services, and much …