Securing the MANET by Detecting the Flooding Attacks Using Hybrid CNN-Bi-LSTM-RF Model
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Publisher
Springer Nature Switzerland
Link
https://link.springer.com/content/pdf/10.1007/978-3-031-44084-7_15
Reference23 articles.
1. Sbai, O., El boukhari, M.: September. Data flooding intrusion detection system for manets using deep learning approach. In: Proceedings of the 13th International Conference on Intelligent Systems: Theories and Applications, pp. 1–5 (2020)
2. Vatambeti, R., Sanshi, S., Krishna, D.P.: An efficient clustering approach for optimized path selection and route maintenance in mobile ad hoc networks. J Ambient Intell Human Comput 14, 305–319 (2023). https://doi.org/10.1007/s12652-021-03298-3
3. Nandi, M., Anusha, K.: An optimized and hybrid energy aware routing model for effective detection of flooding attacks in a manet environment. Wireless Personal Communications, pp.1–19 (2021)
4. Archana, H.P., Khushi, C., Nandini, P., Sivaraman, E., Honnavalli, P.: Cloud-based Network Intrusion Detection System using Deep Learning. ArabWIC 2021: The 7th Annual International Conference on Arab Women in Computing in Conjunction with the 2nd Forum of Women in Research, Sharjah, UAE (2021). https://doi.org/10.1145/3485557.3485562
5. Banerjee, B., Neogy, S.: A brief overview of security attacks and protocols in MANET. In: 2021 IEEE 18th India Council International Conference (INDICON), pp. 1–6. IEEE (2021, December)
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