A Multi - Controller SDN Framework for Advanced Attack Detection and Mitigation in IoT Environment

Authors

  • Mrs. Roselin Lourd. J Head of the Department, Department of Computer Science and Engineering, RAAK College of Engineering and Technology, Puducherry, India Author
  • Dineshkumar. T UG Scholar, Department of Computer Science and Engineering, RAAK College of Engineering and Technology, Puducherry, India Author
  • Kaviarasan. S UG Scholar, Department of Computer Science and Engineering, RAAK College of Engineering and Technology, Puducherry, India Author

Keywords:

Multi-Controller SDN, Internet of Things, Distributed Denial of Service attacks, Random Forest Algorithm, Attack Detection, Attack Mitigation, Security, Ensemble Learning, Scalability, Resilience, Adaptive Defense, Proactive Defense

Abstract

This research introduces a pioneering Multi-Controller Software-Defined Networking (SDN) framework meticulously designed for bolstering attack detection and mitigation capabilities within the intricate landscape of Internet of Things (IoT) environments. Leveraging the random forest algorithm, this framework significantly enhances the ability to detect and counter Distributed Denial of Service (DDoS) attacks, a prevalent threat within IoT networks. The proposed Multi-Controller SDN framework orchestrates multiple controllers to collaborate seamlessly, ensuring distributed intelligence and effective collaboration across diverse IoT devices. The integration of the random forest algorithm enables robust and accurate identification of anomalous traffic patterns indicative of potential DDoS attacks. Key aspects of this research include the development and implementation of a scalable and resilient SDN framework capable of dynamically responding to evolving attack vectors within IoT ecosystems. The random forest algorithm, known for its ensemble learning capabilities and adaptability to diverse datasets, is specifically tailored to detect subtle anomalies and patterns associated with DDoS attacks amidst the complexities of IoT traffic. Through comprehensive simulations and practical evaluations, the framework's efficacy in detecting DDoS attacks is rigorously assessed. Results showcase the framework's ability to accurately identify and mitigate DDoS threats in near real-time, demonstrating its potential to fortify IoT networks against such malicious intrusions. This research contributes a novel approach harnessing the power of Multi-Controller SDN architecture and the random forest algorithm to advance the security posture of IoT environments. The proposed framework not only addresses the intricate challenges posed by DDoS attacks but also paves the way for adaptive and proactive defense mechanisms in the ever-evolving landscape of IoT security.

Downloads

Download data is not yet available.

References

Zhao, W., Aldyaflah, I. M., Gangwani, P., Joshi, S., Upadhyay, H., & Lagos, L. (2023). A Blockchain-Facilitated Secure Sensing Data Processing and Logging System. IEEE Access, 11, 21712-21728.

Chen, X., Hu, X., Li, Y., Gao, X., & Li, D. (2018, October). A blockchain based access authentication scheme of energy internet. In 2018 2nd IEEE Conference on Energy Internet and Energy System Integration (EI2) (pp. 1-9). IEEE.

Ezawa, Y., Takita, M., Shiraishi, Y., Kakei, S., Hirotomo, M., Fukuta, Y., ... & Morii, M. (2019, August). Designing authentication and authorization system with blockchain. In 2019 14th Asia Joint Conference on Information Security (AsiaJCIS) (pp. 111-118). IEEE.

Wang, S., Zhu, S., & Zhang, Y. (2018, June). Blockchain-based mutual authentication security protocol for distributed RFID systems. In 2018 IEEE Symposium on Computers and Communications (ISCC) (pp. 00074-00077). IEEE.

Lu, P. J., Yeh, L. Y., & Huang, J. L. (2018, May). An privacy-preserving cross-organizational authentication/authorization/accounting system using blockchain technology. In 2018 IEEE International Conference on Communications (ICC) (pp. 1-6). IEEE.

Fan, Y., Lin, X., Liang, W., Wang, J., Tan, G., Lei, X., & Jing, L. (2022). TraceChain: A blockchain‐based scheme to protect data confidentiality and traceability. Software: Practice and Experience, 52(1), 115-129.

Jeet, R., Kang, S. S., Safiul Hoque, S. M., & Dugbakie, B. N. (2022). Secure model for IoT healthcare system under encrypted blockchain framework. Security and Communication Networks, 2022.

Haque, M. A., Haque, S., Zeba, S., Kumar, K., Ahmad, S., Rahman, M., ... & Ahmed, L. (2023). Sustainable and efficient E-learning internet of things system through blockchain technology. E-Learning and Digital Media, 20427530231156711.

Sharma, P., Moparthi, N. R., Namasudra, S., Shanmuganathan, V., & Hsu, C. H. (2022). Blockchain‐based IoT architecture to secure healthcare system using identity‐based encryption. Expert Systems, 39(10), e12915.

Rehman, A., Abbas, S., Khan, M. A., Ghazal, T. M., Adnan, K. M., & Mosavi, A. (2022). A secure healthcare 5.0 system based on blockchain technology entangled with federated learning technique. Computers in Biology and Medicine, 150, 106019.

Rajadevi, R., Devi, E. R., Latha, R. S., Harshini, S., Ajay, K., & Abinash, M. (2022, January). Secured storing and sharing of medical records based on blockchain. In 2022 International Conference on Computer Communication and Informatics (ICCCI) (pp. 1-5). IEEE.

Qiao, Y., Lan, Q., Zhou, Z., & Ma, C. (2022). Privacy-preserving credit evaluation system based on blockchain. Expert Systems with Applications, 188, 115989.

Singh, S., Rathore, S., Alfarraj, O., Tolba, A., & Yoon, B. (2022). A framework for privacy-preservation of IoT healthcare data using Federated Learning and blockchain technology. Future Generation Computer Systems, 129, 380-388.

Sharma, P., Namasudra, S., Crespo, R. G., Parra-Fuente, J., & Trivedi, M. C. (2023). EHDHE: Enhancing security of healthcare documents in IoT-enabled digital healthcare ecosystems using blockchain. Information Sciences, 629, 703-718.

Chelladurai, U., & Pandian, S. (2022). A novel blockchain based electronic health record automation system for healthcare. Journal of Ambient Intelligence and Humanized Computing, 1-11.

Sharma, P., Namasudra, S., Chilamkurti, N., Kim, B. G., & Gonzalez Crespo, R. (2023). Blockchain-based privacy preservation for IoT-enabled healthcare system. ACM Transactions on Sensor Networks, 19(3), 1-17.

Venkatraman, S., & Parvin, S. (2022). Developing an IoT identity management system using blockchain. Systems, 10(2), 39.

Zhao, Z., Li, X., Luan, B., Jiang, W., Gao, W., & Neelakandan, S. (2023). Secure internet of things (IoT) using a novel brooks Iyengar quantum byzantine agreement-centered blockchain networking (BIQBA-BCN) model in smart healthcare. Information Sciences, 629, 440-455.

Deepa, N., Devi, T., Gayathri, N., & Kumar, S. R. (2022). Decentralized Healthcare Management System Using Blockchain to Secure Sensitive Medical Data for Users. Blockchain Security in Cloud Computing, 265-282.

Ali, A., Almaiah, M. A., Hajjej, F., Pasha, M. F., Fang, O. H., Khan, R., ... & Zakarya, M. (2022). An industrial IoT-based blockchain-enabled secure searchable encryption approach for healthcare systems using neural network. Sensors, 22(2), 572.

Downloads

Published

04-05-2024

Issue

Section

Research Articles

How to Cite

A Multi - Controller SDN Framework for Advanced Attack Detection and Mitigation in IoT Environment. (2024). International Journal of Scientific Research in Science and Technology, 11(3), 71-79. https://ijsrst.com/index.php/home/article/view/IJSRST24112173

Similar Articles

1-10 of 164

You may also start an advanced similarity search for this article.