Machine Learning-Based Distributed Denial of Services (DDoS) Attack Detection in Intelligent Information Systems-Reference-Cited by-同舟云学术

Machine Learning-Based Distributed Denial of Services (DDoS) Attack Detection in Intelligent Information Systems

Published:2023-08-04 Issue:1 Volume:19 Page:1-17
ISSN:1552-6283
Container-title:International Journal on Semantic Web and Information Systems
language:ng
Short-container-title:

Author:

Alhalabi Wadee¹,Gaurav Akshat²,Arya Varsha³,Zamzami Ikhlas Fuad⁴,Aboalela Rania Anwar⁵^ORCID

Affiliation:

1. Immersive Virtual Reality Research Group, Department of Computer Science, King Abdulaziz University, Jeddah, Saudi Arabia

2. Ronin Institute, USA, & UCRD, Chandigarh University, Chandigarh, India

3. Department of Business Administration, Asia University, Taiwan, & Immersive Virtual Reality Research Group, King Abdulaziz University, Jeddah, Saudi Arabia, & Lebanese American University, Beirut, Lebanon, & Center for Interdisciplinary Research at University of Petroleum and Energy Studies (UPES), Dehradun, India

4. Faculty of business, King Abdulaziz University, Rabigh, Saudi Arabia

5. Department Information System, King Abdulaziz University, Rabigh, Saudi Arabia

Abstract

The danger of distributed denial of service (DDoS) attacks has grown in tandem with the proliferation of intelligent information systems. Because of the sheer volume of connected devices, constantly shifting network circumstances, and the need for instantaneous reaction, conventional DDoS detection methods are inadequate for the IoT. In this context, this study aims to survey the current state of the art in the topic by reading relevant articles found in the Scopus database, with a brief overview of the IoT and DDoS as this study examines neural networks and their applicability to DDoS detection. Finally, a decision tree-based model is developed for the detection of DDoS attacks. The analysis sheds light on the present trends and issues in this field and suggests avenues for further study.

Publisher

IGI Global

Subject

Computer Networks and Communications,Information Systems

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