 |
International Journal for Research Trends and Innovation
International Peer Reviewed & Refereed Journals, Open Access Journal
ISSN Approved Journal No: 2456-3315 | Impact factor: 8.14 | ESTD Year: 2016
Scholarly open access journals, Peer-reviewed, and Refereed Journals, Impact factor 8.14 (Calculate by google scholar and Semantic Scholar | AI-Powered Research Tool) , Multidisciplinary, Monthly, Indexing in all major database & Metadata, Citation Generator, Digital Object Identifier(DOI)
|
Issue: December 2025
Volume 10 | Issue 12
Review Result and Publication of Paper within : 2-3 days
Click Here For more DetailsFor Authors
Forms / Download
Published Issue Details
Editorial Board
Other IMP Links
Facts & Figure
Impact Factor : 8.14
Issue per Year : 12
Volume Published : 10
Issue Published : 115
Article Submitted : 19455
Article Published : 8041
Total Authors : 21252
Total Reviewer : 769
Total Countries : 144
Indexing Partner
Licence
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License
|
Published Paper Details
|
|
| Paper Title: | Small rate DDoS Violence Documentation and Protection by SDN built on Machine Learning Technique |
| Authors Name: | Shibi. M. S , Suresh A.T.K. , Nisha M.D , P Ebby Darney |
| Download E-Certificate: | Download |
| Author Reg. ID: |
IJRTI_187161
|
| Published Paper Id: | IJRTI2306054 |
| Published In: | Volume 8 Issue 6, June-2023 |
| DOI: | |
| Abstract: | Application defined networking architectural framework eases the life of the network administrators by isolating the data plane from the control plane. This facilitates easy configuration of the network, provides a programmable interface for developing applications related to management, security, logging etc. and the centralized logical controller gives more control over the entire network, which has the total visibility of the network. These advantages of SDN also expose the network to the vulnerabilities and therefore the impact of the attacks are much severe in comparison to standard networks, where the network devices in itself provided protection against different attacks and limits the scope of the safety threats. During this paper, we explore various attacks which will be launched on SDN controller at different layers and secure the SDN against threats. A Distributed Denial of Service (DDoS) Violence may be a DoS Violence utilizing multiple distributed Violence sources. Increase in randomness causes decrease in vulnerabilities of system. To extenuate this threat, this paper proposes to use different techniques for the central control of SDN for various Violence detection and introduces an answer that's effective and light-weight in terms of the resources that it uses. More precisely, this project shows how DDoS attacks can exhaust controller resources and provides an answer to detect such attacks supported the variation of the destination IP address. Gridlock characteristics through statistical flow table information and uses the support vector machines (SVM) method to identify the Violence gridlock. The experiment is conducted using KDD99 dataset |
| Keywords: | Application defined networking architectural framework eases the life of the network administrators by isolating the data plane from the control plane. This facilitates easy configuration of the network, provides a programmable interface for developing applications related to management, security, logging etc. and the centralized logical controller gives more control over the entire network, which has the total visibility of the network. These advantages of SDN also expose the network to the vulnerabilities and therefore the impact of the attacks are much severe in comparison to standard networks, where the network devices in itself provided protection against different attacks and limits the scope of the safety threats. During this paper, we explore various attacks which will be launched on SDN controller at different layers and secure the SDN against threats. A Distributed Denial of Service (DDoS) Violence may be a DoS Violence utilizing multiple distributed Violence sources. Increase in randomness causes decrease in vulnerabilities of system. To extenuate this threat, this paper proposes to use different techniques for the central control of SDN for various Violence detection and introduces an answer that's effective and light-weight in terms of the resources that it uses. More precisely, this project shows how DDoS attacks can exhaust controller resources and provides an answer to detect such attacks supported the variation of the destination IP address. Gridlock characteristics through statistical flow table information and uses the support vector machines (SVM) method to identify the Violence gridlock. The experiment is conducted using KDD99 dataset |
| Cite Article: | "Small rate DDoS Violence Documentation and Protection by SDN built on Machine Learning Technique ", International Journal of Science & Engineering Development Research (www.ijrti.org), ISSN:2455-2631, Vol.8, Issue 6, page no.336 - 344, June-2023, Available :http://www.ijrti.org/papers/IJRTI2306054.pdf |
| Downloads: | 000205159 |
| ISSN: |
2456-3315 | IMPACT FACTOR: 8.14 Calculated By Google Scholar| ESTD YEAR: 2016 An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.14 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator |
| Publication Details: |
Published Paper ID: IJRTI2306054
Registration ID:187161
Published In: Volume 8 Issue 6, June-2023
DOI (Digital Object Identifier):
Page No: 336 - 344 Country: kuzhthurai, Tamil Nadu, India Research Area: Engineering Publisher : IJ Publication Published Paper URL : https://www.ijrti.org/viewpaperforall?paper=IJRTI2306054 Published Paper PDF: https://www.ijrti.org/papers/IJRTI2306054 |
| Share Article: | |
|
Click Here to Download This Article |
|
| Article Preview | |
|
|
|
Major Indexing from www.ijrti.org
| Google Scholar | ResearcherID Thomson Reuters | Mendeley : reference manager | Academia.edu |
| arXiv.org : cornell university library | Research Gate | CiteSeerX | DOAJ : Directory of Open Access Journals |
| DRJI | Index Copernicus International | Scribd | DocStoc |
ISSN Details
 |
 |
|
ISSN: 2456-3315
Impact Factor: 8.14 and ISSN APPROVED,
Journal Starting Year (ESTD) : 2016
DOI (A digital object identifier)
| Providing A digital object identifier by DOI.ONE How to Get DOI? |
Conference
Open Access License Policy
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License
Important Details
Join RMS/Earn 300
WhatsApp
Click Here
Click Here
Indexing Partner |
|||
| Copyright © 2025 - All Rights Reserved - IJRTI | |||