Concerns about cybersecurity and attack methods have risen in the information age. Many
techniques are used to detect or deter attacks, such as intrusion detection systems (IDSs) …

Intrusion detection is a key topic in cybersecurity. It aims to protect computer systems and
networks from intruders and malicious attacks. Traditional intrusion detection systems (IDS) …

Intrusion Detection and the ability to detect attacks is a crucial aspect to ensure
cybersecurity. However, what if an IDS (Intrusion Detection System) itself is attacked; in other …

Cyber-security is the practice of protecting computing systems and networks from digital
attacks, which are a rising concern in the Information Age. With the growing pace at which …

Intrusion Detection Systems (IDS) are increasingly adopting machine learning (ML)-based
approaches to detect threats in computer networks due to their ability to learn underlying …

Abstract Machine Learning (ML) can be incredibly valuable to automate anomaly detection
and cyber-attack classification, improving the way that Network Intrusion Detection (NID) is …

The incremental diffusion of machine learning algorithms in supporting cybersecurity is
creating novel defensive opportunities but also new types of risks. Multiple researches have …

Abstract The rise of Adversarial Machine Learning (AML) attacks is presenting a significant
challenge to Intrusion Detection Systems (IDS) and their ability to detect threats. To address …

Network-based Intrusion Detection System (NIDS) forms the frontline defence against
network attacks that compromise the security of the data, systems, and networks. In recent …

Intrusion detection systems are an essential part of any cybersecurity architecture. These
systems are critical in defending networks against a variety of security threats. In recent …