Novel prediction mechanism for Attack Prevention in Fiber-Optical Networks using AI-based SDN

Authors

  • Amanveer Singh, Pooja Grover, Anupam Kumar Gautam, Beemkumar Nagappan, Neeraj Sharma

Keywords:

Attack Prevention, Artificial Intelligence (AI) Based Software-Defined Networking (SDN), Fiber-Optical Networks, Prediction Mechanism, Sea Lion fine-tuned Long Short-Term Memory (SL-FLSTM),

Abstract

Fiber-optical networks enhance communication by delivering data through light signals, which leads to fast and secure communication. Technological advancements provide difficulties, such as the exposure of Artifiical Intelligence (AI) based Software-Defined Networking (SDN) to attacks of distributed denial-of-service (DDoS). The integration of fiber-optical networks and AI-powered SDN highlights the essential requirement for comprehensive cyber security regulations to protect the integrity of current communication infrastructure. In this research, we developed an innovative strategy named Sea Lion fine-tuned Long Short-Term Memory (SL-FLSTM) to predict the attacks of DDoS in fiber-optical networks. Initially, we gathered a dataset which includes fiber optic network communication traffic with various types of DDoS attacks, to train our proposed approach. Our suggested SL-FLSTM incorporates insights from Sea Lion (SL) behavior to improve sequential data processing; it integrates bio-inspired modifications into the LSTM architecture, improving long-term dependency modeling. Min-max normalization algorithm is used to pre-process the gathered raw data, for enhancing the quality of the data. The suggested approach is implemented in Python software. The result evaluation phase is performed with multiple parameters including recall (98.1%), precision (98.2%), F1 score (98.3%) and accuracy (98.4%) to evaluate the suggested SL-FLSTM approach with other conventional methodologies. The experimental results demonstrate that the proposed SL-FLSTM approach performed better than other existing approaches in predicting DDoS attacks in fiber-optical networks.

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References

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Published

26.03.2024

How to Cite

Beemkumar Nagappan, Neeraj Sharma, A. S. P. G. A. K. G. . (2024). Novel prediction mechanism for Attack Prevention in Fiber-Optical Networks using AI-based SDN. International Journal of Intelligent Systems and Applications in Engineering, 12(21s), 1408–1414. Retrieved from https://www.ijisae.org/index.php/IJISAE/article/view/5609

Issue

Vol. 12 No. 21s (2024)

Section

Research Article

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