## 1 Introduction  
Cybercime emerged several years ago. During that era, safeguarding the digital realm was simpler due to the limited number of machines in the digital domain, and the assaults were less intricate compared to the present scenario [1]. However, in recent years, regular world transactions have been transferred into the digital environment due to its ease of use and low cost, and due to new technological advancements. Moreover, the progression of technology has empowered cybercriminals to construct automated tools for executing advanced cyber attacks, particularly targeting wireless networks over time [2]. The usage of social media, blockchain, online banking, cloud environment, Internet of Things (IoT) devices, and wireless communication is increasing rapidly as well. Users and companies started to use wireless communication more than normal wire communication on the computer network. The increased usage of wireless communication technology also raised the amount of research in this domain. Wireless local area networks are the most widely used wireless communication technologies in this field. In general, the use of wireless local area networks has been growing quickly recently and the continuation of this increase is expected in the coming years [3]. On the other hand, the existing condition of wireless local area network technologies renders the utilized network susceptible to a wide range of cyberattacks from passive to active. It is difficult for similar attacks to occur physically because there are situations where the cyberattacker must physically access network cables or traverse several lines, whereas attacks on a wireless local area network can come from any direction and target any node. Examples of these attacks are leaking confidential information, message contamination, and legal impersonation. With the evolution of novel attack mechanisms, it is now feasible to breach someone's financial system, puloin sensitive data from major corporations, encrypt computer data on hard drives, and impede access to substantial corporate resources through DDoS attacks. The financial cost of these incidents sums up to trillions of US dollars globally each year [4]. Furthermore, the rise of new gadgets like smartphones and IoT devices has expanded the potential points of attack in the wireless arena. Cybertiminals persistently refine existing intrusion tactics by crafting diverse iterations and employing novel attack variations [5] tailored for smartphones and IoT devices. To protect communication networks, and especially wireless networks, from attackers, IDSs (intrusion detection systems) have been used for a long time. However, alongside the rate of development of IDSs, the types and severity of attacks against those networks are increasing at a similar rate as well [6]. An intrusion detection system is software that monitors the computer network's traffic flows for indication of malicious activities including breaking network protocols, censoring, stealing information, and preventing network services [7]. An IDS monitors inbound and outbound traffic [8] from all devices on the network. IDSs work behind a firewall as another filter to catch suspicious packets. In short, they look for two clues: The first is the capture of signatures of known attacks. The second is to detect occurring declinations from ordered activities. An IDS generally depends on pattern correlation to determine attacks. Thanks to this technique, an intrusion detection system can compare packets on the network with a database containing signatures of known attack types. The attacks that an IDS can identify by pattern correlation are commonly known attacks such as worms, ransomware, trojans, viruses, and bots [1]. When an IDS detects an abnormal situation, the system marks the suspicious activity and triggers the alarm. The type of this alert can change from a basic node in an audit log to an emergency alert mail sent to an IT administrator.