Journal of Cyber Security DOI:10.32604/jcs.2021.018623 This work is licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Article Computational Intelligent Techniques To Detect DDOS Attacks : A Survey Isha Sood * and Varsha Sharma School of Information Technology, Rajiv Gandhi Prodyogiki Vishvavidyalya, Bhopal, India * Corresponding Author: Isha Sood. Email: Ishasweet1984@gmail.com Received: 06 July 2021; Accepted: 15 July 2021 Abstract: The Internet is often targeted by the Distributed Denial of Service (DDOS) Attacks that deliberately utilize resources and bandwidth to prohibit access to potential users. The attack possibility is that the packets are filled massively. A DOS attack is launched by a single source, while a DDOS attack is originated from numerous resources. DDoS attacks are not capable of stealing website user’s information. The prime motive of the DDoS attacks is to devastate the website resources. Distributed Denial of Service (DDoS) attacks are disruptive to internet access on the Network. The attitude of the customer to get fast and reliable services can be seriously influenced by DDoS attackers. In the digital era of today, cases of DDoS attacks have also been exceeded in the wireless, smartphone, and IoT attacks with catastrophic implications. We will soon be experiencing the 5G smartphone rebellion, but there are indications that 5G networks too are becoming victim to DDoS attacks but the existing DDoS detection and protection strategies are not able to handle DDOS attacks successfully therefore, thorough research on implementing computational intelligent strategies in the detection and defense techniques has been performed to recognize, mitigate, and avoid these attacks. But the most suitable and efficient defense strategy for these attacks remains an issue to be addressed in the future. This review article concentrates on the most prevalent methods of detection and defense against DDoS attacks that incorporate computational intelligence. The analysis describes attacks and explains them. The key factors relevant to the detection of DDOS attacks are included in this research like methods, tools, and detection accuracy. Finally, various challenges attached to the detection of DDOS attacks and research gaps are depicted. Keywords: 5G; DDoS; IoT 1 Introduction Denial-of-Service (DDoS) attack relates to the need for client/server infrastructure to combine multiple devices as an attack tool to promote attacks on one or more objectives to maximize the attack power [1]. It is hard to differentiate attack or acceptable behavior via protocol and services. It becomes difficult to identify a distributed denial-of-service attack [2]. A study on security methods against DDoS attacks at various points in history is largely based on the strategy of detecting network intrusions. Based on the features of many-to-one attacks in the DDoS attack method, three characteristics involving the numbers of source IP addresses, the numbers of target ports as well as the flow density were used to characterize the features of the attack. There are mainly three types of attacks, i.e., Application layer attacks, Protocol attacks, and Volumetric attacks [3].