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Reference

[1].Salmi, S., Oughdir, L. Performance evaluation of deep learning techniques for DoS attacks detection in wireless sensor network. J Big Data 10, 17 (2023). https://doi.org/10.1186/s40537-023-00692-w

 

[2]. Mariam Ibrahim, Ruba Elhafiz, Modeling an intrusion detection using recurrent neural networks,

Journal of Engineering Research,Volume 11, Issue 1,2023,100013,ISSN 2307-1877,

https://doi.org/10.1016/j.jer.2023.100013.

 

[3]. Jullian, O., Otero, B., Rodriguez, E. et al. Deep-Learning Based Detection for Cyber-Attacks in IoT Networks: A Distributed Attack Detection Framework. J Netw Syst Manage 31, 33 (2023). https://doi.org/10.1007/s10922-023-09722-7

 

[4]. R. Doshi, N. Apthorpe and N. Feamster, "Machine Learning DDoS Detection for Consumer Internet of Things Devices," 2018 IEEE Security and Privacy Workshops (SPW), San Francisco, CA, USA, 2018, pp. 29-35, doi: 10.1109/SPW.2018.00013. 

 

[5]. C. Yin, Y. Zhu, J. Fei and X. He, "A Deep Learning Approach for Intrusion Detection Using Recurrent Neural Networks," in IEEE Access, vol. 5, pp. 21954-21961, 2017, doi: 10.1109/ACCESS.2017.2762418.

 

[6] Data Set:  NSL-KDD Data Set [Online]. Available: https://web.archive.org/web/ 20150205070216/http://nsl.cs.unb.ca/NSL-KDD/.

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