There are certain attacks that can be carried out using either TCP or UDP like DNS, LDAP, NETBIOS and SNMP.Įxploitation-based attacks: Are those kinds of attacks in which the identity of the attacker remains hidden by utilizing legitimate third-party component. As Figure 1 shows, in this category, TCP based attacks include MSSQL, SSDP while as UDP based attacks include CharGen, NTP and TFTP. These attacks can be carried out through application layer protocols using transport layer protocols, i.e., Transmission control protocol (TCP), User datagram protocol (UDP) or through a combination of both. The packets are sent to reflector servers by attackers with source IP address set to target victim’s IP address to overwhelm the victim with response packets. Reflection-based DDoS: Are those kinds of attacks in which the identity of the attacker remains hidden by utilizing legitimate third-party component. The rest of this sub-section has been explained the detailed taxonomy of DDoS attacks and illustrated in Figure 1, in terms of reflection-based and exploitation-based attacks. Hence, we have analyzed new attacks that can be carried out using TCP/UDP based protocols at the application layer and proposed a new taxonomy. There is a need to identify new attacks and come up with new taxonomies. Although all have done a commendable job in proposing new taxonomies, the scope of attacks has so far been limited. There are a number of survey studies that have proposed taxonomies with respect to DDoS attacks. Finally, we provide the most important feature sets to detect different types of DDoS attacks with their corresponding weights.

Thirdly, using the generated dataset, we propose a new detection and family classification approach based on a set of network flow features. Secondly, we generate a new dataset, namely CICDDoS2019, which remedies all current shortcomings. In this paper, we first review the existing datasets comprehensively and propose a new taxonomy for DDoS attacks. Although many statistical methods have been designed for DDoS attack detection, designing a real-time detector with low computational overhead is still one of the main concerns. On the other hand, the evaluation of new detection algorithms and techniques heavily relies on the existence of well-designed datasets. Distributed Denial of Service (DDoS) attack is a menace to network security that aims at exhausting the target networks with malicious traffic.

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