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  Published Paper Details:

  Paper Title

DETECTION OF DISTRIBUTED DENIAL OF SERVICE ATTACKS IN SDN USING MACHINE LEARNING TECHNIQUES

  Authors

  M. Rakesh Reddy,  P. V. Abhi Ram,  V. Balu

  Keywords

Attacks, DDoS, Decision Tree SDN.

  Abstract


The term "software-defined network" (SDN) refers to a network architecture that is used to digitally construct and create hardware components. The network connection settings can be changed dynamically. Because the link is fixed in the traditional network, dynamic change is not possible. SDN is a wonderful strategy, but DDoS attacks can still happen. The DDoS assault poses a threat to the internet. The machine learning algorithm can be used to stop DDoS attacks. The DDoS attack is when several systems work together to simultaneously target a certain host. In SDN, the infrastructure layer's devices are controlled by software from the control layer, which sits in the middle of the application and infrastructure layers. We suggest a machine learning method called Decision Tree in this research to identify malicious communications. The results of our test indicate that the Decision Tree can determine if an attack is safe or not.

  IJCRT's Publication Details

  Unique Identification Number - IJCRT2303675

  Paper ID - 232912

  Page Number(s) - f833-f835

  Pubished in - Volume 11 | Issue 3 | March 2023

  DOI (Digital Object Identifier) -   

  Publisher Name - IJCRT | www.ijcrt.org | ISSN : 2320-2882

  E-ISSN Number - 2320-2882

  Cite this article

  M. Rakesh Reddy,  P. V. Abhi Ram,  V. Balu,   "DETECTION OF DISTRIBUTED DENIAL OF SERVICE ATTACKS IN SDN USING MACHINE LEARNING TECHNIQUES", International Journal of Creative Research Thoughts (IJCRT), ISSN:2320-2882, Volume.11, Issue 3, pp.f833-f835, March 2023, Available at :http://www.ijcrt.org/papers/IJCRT2303675.pdf

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ISSN: 2320-2882
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ISSN and 7.97 Impact Factor Details


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ISSN: 2320-2882
Impact Factor: 7.97 and ISSN APPROVED
Journal Starting Year (ESTD) : 2013
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