Mathematical programming and meta-heuristics are two types of optimization methods. Meta-
heuristic algorithms can identify optimal/near-optimal solutions by mimicking natural …

In this paper, we present a review of recent advances in wrapper feature selection
techniques for attack detection and classification, applied in intrusion detection area. Due to …

The increasing trend toward using the Internet of Things (IoT) increased the number of
intrusions and intruders annually. Hence, the integration, confidentiality, and access to …

Nowadays, meta-heuristic algorithms are attracting widespread interest in solving high-
dimensional nonlinear optimization problems. In this paper, a COVID-19 prevention-inspired …

The development and expansion of the Internet and cyberspace have increased computer
systems attacks; therefore, Intrusion Detection Systems (IDSs) are needed more than ever …

Nowadays, the growth and pervasiveness of Internet of Things (IoT) devices have led to
increased attacks by hackers and attackers. On the other hand, using IoT infrastructure in …

Many metaheuristic approaches have been developed to select effective features from
different medical datasets in a feasible time. However, most of them cannot scale well to …

This study relies on using a Moth–Flame Optimization (MFO) method as a search algorithm
and a Decision Tree (DT) as an evaluation algorithm to generate an efficient feature subset …

Intrusion detection systems (IDS) play a crucial role in securing networks and identifying
malicious activity. This is a critical problem in cyber security. In recent years, metaheuristic …

Feature selection (FS) in data mining is one of the most challenging and most important
activities in pattern recognition. In this article, a new hybrid model of whale optimization …