## 1 Introduction  
With the advancement in the development of computers, the network has drastically improved people's day-to-day lives and activities. Apart from this, computing technologies like the cloud, the Internet of Things (IoT), and big data also achieved rapid growth to an indescribable level, and their need has become undeniable [1, 2]. The data being uploaded to these technologies via a network connection undergoes several stages, including creation, transfer, storage, and deletion [3]. The information included in any of these stages is important, particularly related to financial, medical, government, or military applications [4]. With the increase in the number of users associated with the Internet, the circulation of sensitive information on the Internet also increases, which welcomes hackers and attackers to create security threats to the data via several proficient software tools [5]. Also, today's Internet is highly misused by several kinds of attacks, network failures, cases of abuse, and malicious behaviors. Some recent prevalent attacks in the network include worms, denial of service (DoS), and port viewing attacks [6, 7]. All these attacks and malicious behaviors create problems for the network, resulting in resource wastage, security threats to users' sensitive information, and a reduction in the performance of an end host and network equipment [8]. System vulnerability is the specific cause of intrusions occurring in the systems as it paves the way for intruders to destroy, steal, or alter the information, causing damage to the systems associated with the network [9]. Since several attacks threaten the normal functioning of networks and systems, effective security and data privacy mechanisms are urgently needed to overcome future issues [10]. Effective dynamic management of network traffic is crucial to respond effectively to security threats while developing the Internet [11]. Some of the important criteria required to be viewed while developing any security measure include monitoring network performance, accurately understanding network dynamics and operations, meeting most user needs, and ensuring the quality of service (QoS) [12; 13]. While offering security to the network systems, security engineers need to focus on the following terms: confidentiality, integrity, and availability (CIA triad) to ensure better and stable performance [14]. Intrusion detection systems (IDSs) are the ultimate focus of the research community when dealing with any security threats or issues. These systems recently provided beneficial solutions to meet the challenges of malicious behaviors [15]. The IDSs can be software, hardware, or a combination of both, and these are used to detect suspicious activities on the host, known as host-based IDS, or the network, named network-based IDS. The IDSs are categorized into specification-based, signature-based, and anomaly-based IDS [16]. The first category monitors skewness in the incoming network packets using a set of rules, the second category matches the traffic flow with the stored signatures of known attacks, and the final category identifies the threats in the network [17; 18]. With the rapid growth in attacks, the signature-based IDS needs continuous database updates, and the specification-based IDS requires expert knowledge, which is the main drawback. The third type is considered more advanced than the other two types and mainly uses classification algorithms to deal with problems. Upon reviewing the existing mechanisms, it was identified that much work has been done on intrusion detection. Artificial intelligence and machine learning algorithms are preferred to promote the accurate classification of attacks [19; 20]. Several deep learning and machine learning-based methodologies showed better and more efficient performance in accurately identifying the normal and attack instances. Most are subjected to identifying the different types of attacks threatening the network.