Abstract Machine Learning (ML) techniques are becoming an invaluable support for network
intrusion detection, especially in revealing anomalous flows, which often hide cyber-threats …

The widespread use of Android-based smartphones made it an important target for
malicious applications' developers. So, a large number of frameworks have been proposed …

The impact of information security breaching becomes bigger and complicated to ignore
every day. New and more sophisticated attacks are emerging and developed; requiring the …

Abstract Machine learning-based IDSs have demonstrated promising outcomes in
identifying and mitigating security threats within IoT networks. However, the efficacy of such …

Cuttlefish algorithm (CFA) is a metaheuristic bio-inspired algorithm that mimics the color-
changing behavior by the cuttlefish. It is produced by light reflected from different layers of …

Abstract Cross-Site Scripting (XSS) attacks continue to be a significant threat to web
application security, necessitating robust detection mechanisms to safeguard user data and …

An intrusion detection system (IDS) plays an important role in cyber security to detect
network attacks. To improve the effectiveness of IDS, a new intrusion detection approach …

Cybercriminal activities over computer network systems are considered one of the
preponderant issues that humanity will face in the coming two decades. The development …

This paper proposes a novel approach for intrusion detection using a metaheuristic-based
feature selection method combined with convolutional neural networks (CNNs). The feature …

The cloud environment is used in all sectors that provide different services to the users. The
assistance provided by the cloud environment in different sectors such as business …