IoT DDoS Traffic Detection Using Adaptive Heuristics Assisted With Machine Learning

Rahbani, Rani Al; Khalife, Jawad

doi:10.1109/isdfs55398.2022.9800786

Cited by 1 publication

(1 citation statement)

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“…Due to this dependence of human life on the Internet and intelligent systems, attackers target the Internet to affect human life. [7][8][9][10] One of the most popular methods of doing this is through a distributed denial of service (DDoS) attack, 11,12 which generates large fake traffic that can disrupt the normal working of the Internet. DDoS attacks [13][14][15][16] architecture is presented in Figure 1.…”

Section: Introductionmentioning

confidence: 99%

A comprehensive survey on DDoS attacks on various intelligent systems and it's defense techniques

Gaurav

Gupta

Alhalabi

et al. 2022

Int J of Intelligent Sys

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The purpose of this study is to provide an overview of distributed denial of service (DDoS) attack detection in intelligent systems. In recent times, due to the endemic COVID‐19, the use of intelligent systems has increased. However, these systems are easily affected by DDoS attacks. A DDoS attack is a reliable tool for cyber‐attackers because there is no efficient method which can detect or filter it properly. In this context, we analyze different types of DDoS attacks and defense techniques for intelligent systems. For the analysis, we used Scopus databases to collect relevant papers in English between 2014 and 2022. This study makes an important contribution to the field of DDoS attack detection for intelligent systems, providing a comprehensive overview of the field's evolution and current status, as well as a comprehensive, synthesized, and organized summary of various perspectives, definitions, and trends in the field.

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