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Detection of Multi-Vector DDoS Attack

Kunal Kumar Brahma1 , Satyajit Sarmah2 , Chandan Kalita3 , Rajdeep Ghosh4

Section:Research Paper, Product Type: Journal Paper
Volume-7 , Issue-6 , Page no. 847-851, Jun-2019

CrossRef-DOI:   https://doi.org/10.26438/ijcse/v7i6.847851

Online published on Jun 30, 2019

Copyright © Kunal Kumar Brahma, Satyajit Sarmah, Chandan Kalita, Rajdeep Ghosh . 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: Kunal Kumar Brahma, Satyajit Sarmah, Chandan Kalita, Rajdeep Ghosh, “Detection of Multi-Vector DDoS Attack,” International Journal of Computer Sciences and Engineering, Vol.7, Issue.6, pp.847-851, 2019.

MLA Style Citation: Kunal Kumar Brahma, Satyajit Sarmah, Chandan Kalita, Rajdeep Ghosh "Detection of Multi-Vector DDoS Attack." International Journal of Computer Sciences and Engineering 7.6 (2019): 847-851.

APA Style Citation: Kunal Kumar Brahma, Satyajit Sarmah, Chandan Kalita, Rajdeep Ghosh, (2019). Detection of Multi-Vector DDoS Attack. International Journal of Computer Sciences and Engineering, 7(6), 847-851.

BibTex Style Citation:
@article{Brahma_2019,
author = {Kunal Kumar Brahma, Satyajit Sarmah, Chandan Kalita, Rajdeep Ghosh},
title = {Detection of Multi-Vector DDoS Attack},
journal = {International Journal of Computer Sciences and Engineering},
issue_date = {6 2019},
volume = {7},
Issue = {6},
month = {6},
year = {2019},
issn = {2347-2693},
pages = {847-851},
url = {https://www.ijcseonline.org/full_paper_view.php?paper_id=4641},
doi = {https://doi.org/10.26438/ijcse/v7i6.847851}
publisher = {IJCSE, Indore, INDIA},
}

RIS Style Citation:
TY - JOUR
DO = {https://doi.org/10.26438/ijcse/v7i6.847851}
UR - https://www.ijcseonline.org/full_paper_view.php?paper_id=4641
TI - Detection of Multi-Vector DDoS Attack
T2 - International Journal of Computer Sciences and Engineering
AU - Kunal Kumar Brahma, Satyajit Sarmah, Chandan Kalita, Rajdeep Ghosh
PY - 2019
DA - 2019/06/30
PB - IJCSE, Indore, INDIA
SP - 847-851
IS - 6
VL - 7
SN - 2347-2693
ER -

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Abstract

In this current technology driven society, internet has become a basic commodity for every individuals as well as organization. Due to the rapid increase of internet dependency of government offices, private company, or corporate sectors, security has become the main concern in all of these organizations. Attack over the network using stochastic approaches has created large chaos. The DDoS attack has created destruction and damages over the network since early 2000’s. DDoS is known for its ability to fade the identity of the source of attack because of multiple address and flooding mechanism. Preventing the attack from its original source is quite difficult. This floods the whole system making the system of the particular sector to be crippled and can be remedied by early detection of the attack. In this work we try to detect the different DDoS attack vectors and classify it. The nature and its mechanism are studied to identify the type of attack. We use scikit learn, a machine learning approach to detect different forms of attacks.

Key-Words / Index Term

DDoS, vectors, Machine Learning, Confusion Matrix

References

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