Intrusion detection systems (IDSs) employ sophisticated security techniques to detect
malicious activities on hosts and/or networks. IDSs have been utilized to ensure the security …

Traditional ML based IDS cannot handle high-speed and ever-evolving attacks.
Furthermore, these traditional IDS face several common challenges, such as processing …

Intrusion detection is the core topic of network security, and the intrusion detection algorithm
based on deep learning has become a research hotspot in network security. In this paper, a …

The research proposed in this article presents a novel improved version of the widely
adopted firefly algorithm and its application for tuning and optimising XGBoost classifier …

As cyber-attacks become remarkably sophisticated, effective Intrusion Detection Systems
(IDSs) are needed to monitor computer resources and to provide alerts regarding unusual or …

This paper proposes an AI-powered intrusion detection method that improves intrusion
detection performance by increasing the quality of the training set and employing numerous …

Data privacy is essential in the financial sector to protect client's sensitive information,
prevent financial fraud, ensure regulatory compliance, and safeguard intellectual property. It …

From a security perspective, the research of the jeopardized 6G wireless communications
and its expected ultra-densified ubiquitous wireless networks urge the development of a …

Abstract The adoption of Advanced Driver Assistance Systems (ADAS) has expanded
dramatically in recent years, with the goal of improving road safety and driving comfort …

Current intrusion detection systems, which rely on signature-based detection using rules
derived from the inspection of past traffic flows and their signatures, are incapable of …