A DDoS Attack Detection Using Deep Learning - A Review

Author(s)	Kunal Kumar, Atul Barver
Country	India
Abstract	In this review article, the distributed denial of service (DDoS) assaults are the main topic since they offer a substantial danger to systems linked to the internet and can cause large losses in terms of money, bandwidth and downtime. In this review paper discuss the detection approaches, which are used in traditional methods for identifying and mitigating these assaults, have a limited capacity to identify fresh and changing attack patterns. In this review paper, we provide a deep learning-based DDoS assault detection method. Also discuss the different methods presented by different researchers in the last decade for detection of DoS attack in network.
Keywords	Software Define Network (SDN), Distributed Denial of Services (DDoS), Machine Learning and MATLAB.
Field	Computer Applications
Published In	Volume 5, Issue 3, May-June 2023
Published On	2023-05-04
Cite This	A DDoS Attack Detection Using Deep Learning - A Review - Kunal Kumar, Atul Barver - IJFMR Volume 5, Issue 3, May-June 2023. DOI 10.36948/ijfmr.2023.v05i03.2842
DOI	https://doi.org/10.36948/ijfmr.2023.v05i03.2842
Short DOI	https://doi.org/gr7hdc

About IJFMR Fees & Payment Current Issue Publication Archive	Submit Research Paper Track Submission Status Publication Guidelines Publication Ethics Peer Review & Plagiarism	Join as a Reviewer Editors & Reviewers Reviewer Referral Program Get Reviewer Membership Certi.	Website/Journal Policies Usage Policy Content Policies Privacy Policy

Contact Us		+91-9898-5948-55	editor@ijfmr.com

International Journal For Multidisciplinary Research