A comprehensive survey on DDoS detection, mitigation, and defense strategies in software-defined networks

被引：6

作者：

Jain, Ankit Kumar ^{[1
]}

Shukla, Hariom ^{[1
]}

Goel, Diksha ^{[2
]}

机构：

[1] Natl Inst Technol Kurukshetra, Kurukshetra, India

[2] CSIROs Data61, Melbourne, Vic, Australia

来源：

CLUSTER COMPUTING-THE JOURNAL OF NETWORKS SOFTWARE TOOLS AND APPLICATIONS | 2024年 / 27卷 / 09期

关键词：

Software defined network; Distributed denial of service attack; Machine learning; Honeypot; Blockchain; ATTACK DETECTION; SDN; MACHINE; HONEYPOT;

D O I：

10.1007/s10586-024-04596-z

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

Software Defined Networking (SDN) has become increasingly prevalent in cloud computing, Internet of Things (IoT), and various environments to optimize network efficiency. While it provides a flexible network infrastructure, it also faces security threats, particularly from Distributed Denial of Service (DDoS) attacks due to its centralized design. This survey comprehensively reviews the efforts of various researchers in safeguarding SDN against DDoS attacks and analyzes different detection and mitigation strategies employed in SDN environments. Furthermore, the survey explores various types of DDoS attacks that can occur across different planes and communication links in SDN. Additionally, emerging security measures for preventing DDoS attacks in SDN are examined. The survey also reviews the datasets, tools, and simulators used for detecting DDoS attacks in SDN. Moreover, the survey identifies various open challenges in detecting and mitigating DDoS attacks in SDN and outlines potential future research directions. Lastly, the survey provides a comprehensive comparative analysis of various DDoS detection techniques based on various essential parameters.

引用

页码：13129 / 13164

页数：36

共 116 条

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