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Computer network systems are now managed and controlled by complicated architecture. The sheer number of diverse devices that make up the network is the primary cause of this issue. In addition to enabling considerable innovation in communication networks [1]. Distributed Denial of Service (DDoS) attacks are a significant threat to organizations worldwide. These attacks have the potential to paralyze networks, making them inaccessible to legitimate users and causing severe disruptions in service availability and integrity. The ability to detect and mitigate DDoS attacks has therefore become vital to ensuring the resilience and security of critical infrastructure. Given the rising frequency and complexity of DDoS attacks in the cybersecurity landscape, it is imperative to develop effective intrusion detection systems (IDS) to ensure network infrastructure integrity and availability [2]. A DDoS attack targets the victim's assets or adjacent networks because multiple attackers synchronize false data measurements over a large area. This type of attack is launched by taking advantage of system flaws along with unnecessary network traffic to meet certain parameters such as bandwidth, memory and network processing time and cause significant disruption to the target. The attack may have multiple sources, flooding the target with attack packets, or it may have a single source and originate from a single host. Additionally, attack tools have evolved and are now easily accessible online. With the intention that any Internet user may use this technology to launch attacks with little effort [3]. DDoS attacks are one of the major risks to cyber security that are having an increasing impact on online infrastructure and organizations. By sending malicious traffic to servers and network resources, these attacks strain available resources in an attempt to interfere with users' access to services and systems. Recent reports indicate that the number of DDoS attacks is rising, along wit