Adaptive Learning Method for DDoS Attacks on Software Defined Network Function Virtualization

Janarthanam, S. and Prakash, N. and Shanthakumar, M. (2020) Adaptive Learning Method for DDoS Attacks on Software Defined Network Function Virtualization. EAI Endorsed Transactions on Cloud Systems, 6 (18): e6. ISSN 2410-6895

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Abstract

Software Defined Network (SDN) system controller stands with excessive benefits from the separated promoting devices. The SDN will resolve security issues, inheritance community with acute liabilities. The most important exposure is DDoS attack. The goals of this work to endorse a learning technique on DDoS attacks by SDN based system. Disturb the user’s defensible actions elevate to advise Adaptive Learning method (ALM) as advance set of SVM to return certain viabilities. This paper notices two types of flooding-based DDoS attacks. Proposed Virtualization method decreases the exercise and testing time using the key features, namely the volumetric and the asymmetric features. The accurateness of the revealing process is around 97% of fastest practice and investigation time.

Item Type: Article
Uncontrolled Keywords: Denial of Services, Software Defined Network, Support Vector Machine, Virtualization Functions, Networking
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
QA75 Electronic computers. Computer science
Depositing User: EAI Editor II.
Date Deposited: 09 Sep 2020 11:56
Last Modified: 09 Sep 2020 11:56
URI: https://eprints.eudl.eu/id/eprint/138

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