Software Defined Networking Based Protection against DDOS in IOT
P. J. Beslin Pajila1, P. Jenifer2, C. Karpagavalli3, A. Angeline Valentina Sweety4, R. MuthuLakshmi5
1P. J. Beslin Pajila*, Department of Computer Science and Engineering, Francis Xavier Engineering College, Tirunelveli, India.
2Jennifer P., Assistant Professor, Department of Computer Science and Engineering, Francis Xavier Engineering College, Tirunelveli, Tamil Nadu, India.
3Karpagavalli C., Professor, Department of Computer Science and Engineering, St. Mother Theresa Engineering College, Tuticorin, Tamil Nadu, India.
4Angeline Valentina Sweety A., Department of Computer Science and Engineering from Franics Xavier Engineering College, Affiliated to Anna University, Tirunelveli, Tamil Nadu, India.
5Muthu Lakshmni R., Department of Computer Science and Engineering from Franics Xavier Engineering College, Affiliated to Anna University, Tirunelveli, Tamil Nadu, Indi
Manuscript received on February 10, 2020. | Revised Manuscript received on February 25, 2020. | Manuscript published on March 10, 2020. | PP: 739-745 | Volume-9 Issue-5, March 2020. | Retrieval Number: F3340049620/2020©BEIESP | DOI: 10.35940/ijitee.F3340.049620
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Safety has become enormously important with the proliferation of internet of Things(IoT) technologies. Most of the IoT devices are linked with the DDoS attack, there are many risk nowadays for IoT because of DDoS attack. The new software-defined everything(SDx) model offers a way to handle IoT devices securely. The proposed S-IOT framework consists of a pool that includes S-IoT controllers, S-IoT switches and IoT devices. A new ENeFS algorithm is proposed to identify and reduce the DDoS attack. The proposed algorithm uses neuro fuzzy instruct rule to identify the DDoS attack and the number of data packets count also considered for the identification. The simulation results shows that the proposed algorithm performs better to improve the reliability of the IoT with different and unsafe gadgets.
Keywords: Software defined Internet of Things (S-IoT), Distributed Denial of Service (DDoS), attack identification, attack reduction, neuro fuzzy instruct rule.
Scope of the Article: Software Engineering Techniques and Production Perspectives