Malay Kule

Work place: IIEST/CST, Shibpur, 711103, India

E-mail: malay.kule@gmail.com

Website:

Research Interests: Hardware Security, Network Security

Biography

Dr. Malay Kule has been on the faculty of the Indian Institute of Engineering Science and Technology (IIEST), Shibpur, India since 2013, where currently, he is an assistant professor (Grade II) of Computer Science and Technology. Previously he served as an assistant professor in the department of Computer Science and Engineering of St. Thomas’ College of Engineering and Technology, Kolkata, India from 2006 to 2013. He received the B. Sc. degree in physics honours, the B. Tech. and M. Tech. degrees in Computer Science and Engineering, all from the University of Calcutta, India. He received the PhD degree in Engineering from the Indian Institute of Engineering Science and Technology, Shibpur, India. His research interest includes defect tolerance of nanoscale crossbar circuits, cryptology, hardware security, and Social Network Security

Author Articles
An Efficient Approach for Detection of Compromised SDN Switches and Restoration of Network Flow

By Tinku Adhikari Ajoy Kumar Khan Malay Kule Subhajit Das

DOI: https://doi.org/10.5815/ijcnis.2024.05.05, Pub. Date: 8 Oct. 2024

In Software Defined Networking (SDN) the data plane is separated from the controller plane to achieve better functionality than the traditional networking. Although this approach poses a lot of security vulnerabilities due to its centralized approach. One significant issue is compromised SDN switches because the switches are dumb in SDN architecture and in absence of any intelligence it can be a easy target to the attackers. If one or more switches are attacked and compromised by the attackers, then the whole network might be down or defunct. Therefore, in this work we have devised a strategy to successfully detect the compromised SDN switches, isolate them and then reconstruct the whole network flow again by bypassing the compromised switches. In our proposed approach of detection, we have used two controllers, one as primary and another as secondary which is used to run and validate our algorithm in the detection process. Flow reconstruction is the next job of the secondary controller which after execution is conveyed to the primary controller. A two-controller strategy has been used to balance the additional load of detection and reconstruction activity from the master controller and thus achieved a balanced outcome in terms of running time and CPU utilization. All the propositions are validated by experimental analysis of the results and compared with existing state of the art to satisfy our claim.

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