Benchmark datasets are heavily depended upon by the research community to validate
theoretical findings and track progression in the state-of-the-art. NIDS dataset creation …

With the growing processing power of computing systems and the increasing availability of
massive datasets, machine learning algorithms have led to major breakthroughs in many …

Machine Learning (ML) represents a pivotal technology for current and future information
systems, and many domains already leverage the capabilities of ML. However, deployment …

As computer networks and interconnected systems continue to gain widespread adoption,
ensuring cybersecurity has become a prominent concern for organizations, regardless of …

Technology is pivotal in the rapid growth of services and intensifying the quality of life.
Recent technology, like the Internet of Things (IoT), demonstrates an impressive …

Abstract Detecting attacks to Cyber-Physical Systems (CPSs) is of utmost importance, due to
their increasingly frequent use in many critical assets. Intrusion detection in CPSs and other …

Despite decades of research in network traffic analysis and incredible advances in artificial
intelligence, network intrusion detection systems based on machine learning (ML) have yet …

The constantly evolving digital transformation imposes new requirements on our society.
Aspects relating to reliance on the networking domain and the difficulty of achieving security …

Abstract Machine Learning (ML)-based network intrusion detection systems bring many
benefits for enhancing the cybersecurity posture of an organisation. Many systems have …

Intrusion detection is a primary concern in any modern computer system due to the ever-
growing number of intrusions. Machine learning represents an effective solution to detect …