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A Survey of DDoS Attack Detection Schemes: Methods, Challenges, and Datasets

V. Sughanthini1 , P. Bharathisindhu2

  1. Dept. of Computer Science, Vellalar College for Women in Thindal, Erode, India.
  2. Dept. of Computer Science, Vivekanandha Arts and Science College for Women, India.

Section:Survey Paper, Product Type: Journal Paper
Volume-12 , Issue-4 , Page no. 68-74, Apr-2024

CrossRef-DOI:   https://doi.org/10.26438/ijcse/v12i4.6874

Online published on Apr 30, 2024

Copyright © V. Sughanthini, P. Bharathisindhu . This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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IEEE Style Citation: V. Sughanthini, P. Bharathisindhu, “A Survey of DDoS Attack Detection Schemes: Methods, Challenges, and Datasets,” International Journal of Computer Sciences and Engineering, Vol.12, Issue.4, pp.68-74, 2024.

MLA Style Citation: V. Sughanthini, P. Bharathisindhu "A Survey of DDoS Attack Detection Schemes: Methods, Challenges, and Datasets." International Journal of Computer Sciences and Engineering 12.4 (2024): 68-74.

APA Style Citation: V. Sughanthini, P. Bharathisindhu, (2024). A Survey of DDoS Attack Detection Schemes: Methods, Challenges, and Datasets. International Journal of Computer Sciences and Engineering, 12(4), 68-74.

BibTex Style Citation:
@article{Sughanthini_2024,
author = {V. Sughanthini, P. Bharathisindhu},
title = {A Survey of DDoS Attack Detection Schemes: Methods, Challenges, and Datasets},
journal = {International Journal of Computer Sciences and Engineering},
issue_date = {4 2024},
volume = {12},
Issue = {4},
month = {4},
year = {2024},
issn = {2347-2693},
pages = {68-74},
url = {https://www.ijcseonline.org/full_paper_view.php?paper_id=5681},
doi = {https://doi.org/10.26438/ijcse/v12i4.6874}
publisher = {IJCSE, Indore, INDIA},
}

RIS Style Citation:
TY - JOUR
DO = {https://doi.org/10.26438/ijcse/v12i4.6874}
UR - https://www.ijcseonline.org/full_paper_view.php?paper_id=5681
TI - A Survey of DDoS Attack Detection Schemes: Methods, Challenges, and Datasets
T2 - International Journal of Computer Sciences and Engineering
AU - V. Sughanthini, P. Bharathisindhu
PY - 2024
DA - 2024/04/30
PB - IJCSE, Indore, INDIA
SP - 68-74
IS - 4
VL - 12
SN - 2347-2693
ER -

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Abstract

Cloud computing makes use of a significant amount of virtual storage to provide services on demand via the Internet. The main benefits of cloud computing are reduced service costs and the elimination of the need for consumers to set up expensive computer hardware. The rapid integration of cloud computing with business and numerous other domains has prompted scholars to investigate novel, related technologies. Because of the cloud storage server`s scale and accessibility, individual businesses and users bring their apps, data, and facilities to it for computing operations. Despite the advantages, switching from local to remote computing has created several challenges and security issues for service providers as well as clients. The cloud service provider uses several web technologies to supply its services via the Internet, raising fresh security concerns. The DDoS assault, which aims to prevent legitimate users from accessing a target system or network by overloading it with traffic, is the most serious security issue in cloud computing. In light of this, the article covers the principles of cloud computing, as well as its various forms, security concerns, DDoS assaults, and methods for detecting them using performance metrics and datasets. Lastly, a discussion of cloud computing`s difficulties is included.

Key-Words / Index Term

Cloud Computing, Distributed Denial of Services (DDoS), DDoS attack Detection; Machine learning; Deep learning

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