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ISSN Approved Journal No: 2320-2882 | Impact factor: 7.97 | ESTD Year: 2013
Call For Paper - Volume 14 | Issue 3 | Month- March 2026
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Published Paper Details:
Paper Title
Evaluating Ensemble Bagging Techniques in Software-Defined Networks for Detecting Distributed Denial of Service Attacks
Authors
Ashish kumar tiwari, ASEEM MISHRA, VIKAS SHUKLA
Keywords
Software Defined Networking, Distributed Denial Of Service Attacks, Machine Learning Algorithms, K-Nearest Neighbor.
Abstract
Software-Defined Networking (SDN) separates control functions from data forwarding, allowing for dynamic updates to network rules and enhancing overall network management and control. However, centralized control in SDN remains a significant challenge for researchers, as it is susceptible to various attacks, including Distributed Denial of Service (DDoS) attacks. To address this issue, this paper proposes a DDoS detection solution that leverages the K-Nearest Neighbor (KNN) machine learning algorithm to identify DDoS attacks within SDN environments. The experiment involved testing the KNN algorithm with different values of k to analyze its effectiveness and identify the optimal k value that delivers the most accurate results.
IJCRT's Publication Details
Unique Identification Number - IJCRT2412737
Paper ID - 273879
Page Number(s) - g691-g697
Pubished in - Volume 12 | Issue 12 | December 2024
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Publisher Name - IJCRT | www.ijcrt.org | ISSN : 2320-2882
E-ISSN Number - 2320-2882
Cite this article
Ashish kumar tiwari, ASEEM MISHRA, VIKAS SHUKLA, "Evaluating Ensemble Bagging Techniques in Software-Defined Networks for Detecting Distributed Denial of Service Attacks", International Journal of Creative Research Thoughts (IJCRT), ISSN:2320-2882, Volume.12, Issue 12, pp.g691-g697, December 2024, Available at :http://www.ijcrt.org/papers/IJCRT2412737.pdf
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Submit Manuscript Online Impact Factor: 7.97 Review Results : Within 02-03 Days Paper Publication : Within 02-03 Days
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ISSN: 2320-2882 Impact Factor: 7.97 and ISSN APPROVED Journal Starting Year (ESTD) : 2013
ISSN and 7.97 Impact Factor Details
ISSN: 2320-2882 Impact Factor: 7.97 and ISSN APPROVED Journal Starting Year (ESTD) : 2013
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