Improving intrusion detection using LSTM-RNN to protect drones’ networks

Author:

Gamal Menna,Elhamahmy MohamedORCID,Taha Sanaa,Elmahdy Hesham

Publisher

Elsevier BV

Reference18 articles.

1. An intrusion detection system for drone swarming utilizing timed probabilistic automata;Venkatraman;Drones,2023

2. A comprehensive survey on security, privacy issues and emerging defence technologies for UAVs;Hassan;J Netw Comput Appl,2023

3. Murat B, Elgiz B, Daniel D, Stéphane P. Real-time fault detection on small fixed-Wing UAVa using machine learning. In: the proceedings of the 2020 AIAA/IEEE 39th Digital Avionics Systems Conference (DASC), pp.: 1–10, San Antonio, TX, USA, 11–16 October 2020.

4. Ahmad A, Zouhair D. Using MLSTM and multioutput convolutional LSTM algorithms for detecting anomalous patterns in streamed data of unmanned aerial vehicles, IEEE Aerospace and Electronic Systems Magazine, vol. 37, no. 6, pp. 6-15, 1 June 2022. Doi: 10.1109/MAES.2021.3053108.

5. An efficient attack detection for Intrusion Detection System (IDS) in the internet of medical things smart environment with deep learning algorithm;Fatimah;J Theor Appl Inf Technol,2023

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