Secured Federated Learning for DDoS Detection in Heterogenous Telecom Cloud Networks Using Recurrent Neural Networks

International Journal of Electrical and Electronics Engineering

© 2023 by SSRG - IJEEE Journal

Volume 10 Issue 12

Year of Publication : 2023

Authors : Abdoul-Aziz Maiga, Edwin Ataro, Stanley Githinji

10.14445/23488379/IJEEE-V10I12P106

How to Cite?

Abdoul-Aziz Maiga, Edwin Ataro, Stanley Githinji, "Secured Federated Learning for DDoS Detection in Heterogenous Telecom Cloud Networks Using Recurrent Neural Networks," SSRG International Journal of Electrical and Electronics Engineering, vol. 10,  no. 12, pp. 54-64, 2023. Crossref, https://doi.org/10.14445/23488379/IJEEE-V10I12P106

Abstract:

The recent evolution of cloud computing has enabled the cloudification of Telecommunication (Telecom) network functions. The cloud-based Telecom infrastructure is more scalable, flexible, and cost-efficient for service providers. However, a significant security challenge for Telecom cloud providers is ensuring the availability of services provided to users by mitigating Distributed Denial of Service (DDoS) attacks. The fact that Virtual Network Functions (VNF) in the Telecom cloud are hosted on the Internet makes them easy targets for large-scale DDoS attacks. This study proposes the use of secured supervised Federated Learning (FL) with an efficient Hybrid Recurrent Neural Network (H-RNN) for DDOS attack mitigation in the Telecom cloud. The proposed H-RNN model combines LSTM, a Bidirectional GRU (BiGRU), and a Bidirectional LSTM (BiLSTM) to obtain a state-of-the-art LSTM+BiGRU+BiLSTM model. FL is used with Secure Sockets Layer (SSL) encryption, which supports data privacy and integrity in heterogeneous Telecom cloud networks. The simulation results using the CICDDOS2019 benchmark dataset displayed a detection accuracy of 99.59%, a False Positive Rate (FPR) of 0.042%, and an average detection time of 0.062 ms. A novel H-RNN model and secured FL are proposed to enable deep-learning-based anti-DDoS technology building and deployment in cloud-based Telecom networks.

Keywords:

DDoS attack mitigation, Deep Learning, Federated Learning, SSL, Telecom cloud.

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