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Submarine Hunter: Efficient and Secure Multi-Type Unmanned Vehicles

Halah Hasan Mahmoud1, Marwan Kadhim Mohammed Al-Shammari1, Gehad Abdullah Amran2,3,*, Elsayed Tag eldin4,*, Ala R. Alareqi5, Nivin A. Ghamry6, Ehaa ALnajjar7, Esmail Almosharea8

1 Computer Center, University of Baghdad, Baghdad, 6751, Iraq
2 Department of Management Science and Engineering, Dalian University of Technology, Liaoning, Dalian, 116024, China
3 Department of Information Technology Faculty of Computer Sciences and Information Technology, AL Razi University, Sana’a, Yemen
4 Faculty of Engineering and Technology, Future University in Egypt, New Cairo, 11835, Egypt
5 Faculty of Engineering Mechanics, Dalian University of Technology, Liaoning, Dalian, 116024, China
6 Faculty of Computers and Artificial Intelligence, Cairo University, Giza, Egypt
7 Department of Business Administration, Dalian University of Technology, Liaoning, Dalian, 116024, China
8 College of Software Engineering, Dalian University of Technology, China

* Corresponding Authors: Gehad Abdullah Amran. Email: email; Elsayed Tag eldin. Email: email

(This article belongs to the Special Issue: Intelligent Technologies and Applications for Future Wireless Communications)

Computers, Materials & Continua 2023, 76(1), 573-589.


Utilizing artificial intelligence (AI) to protect smart coastal cities has become a novel vision for scientific and industrial institutions. One of these AI technologies is using efficient and secure multi-environment Unmanned Vehicles (UVs) for anti-submarine attacks. This study’s contribution is the early detection of a submarine assault employing hybrid environment UVs that are controlled using swarm optimization and secure the information in between UVs using a decentralized cybersecurity strategy. The Dragonfly Algorithm is used for the orientation and clustering of the UVs in the optimization approach, and the Re-fragmentation strategy is used in the Network layer of the TCP/IP protocol as a cybersecurity solution. The research’s noteworthy findings demonstrate UVs’ logistical capability to promptly detect the target and address the problem while securely keeping the drone’s geographical information. The results suggest that detecting the submarine early increases the likelihood of averting a collision. The dragonfly strategy of sensing the position of the submersible and aggregating around it demonstrates the reliability of swarm intelligence in increasing access efficiency. Securing communication between Unmanned Aerial Vehicles (UAVs) improves the level of secrecy necessary for the task. The swarm navigation is based on a peer-to-peer system, which allows each UAV to access information from its peers. This, in turn, helps the UAVs to determine the best route to take and to avoid collisions with other UAVs. The dragonfly strategy also increases the speed of the mission by minimizing the time spent finding the target.


Cite This Article

APA Style
Mahmoud, H.H., Al-Shammari, M.K.M., Amran, G.A., eldin, E.T., Alareqi, A.R. et al. (2023). Submarine hunter: efficient and secure multi-type unmanned vehicles. Computers, Materials & Continua, 76(1), 573-589.
Vancouver Style
Mahmoud HH, Al-Shammari MKM, Amran GA, eldin ET, Alareqi AR, Ghamry NA, et al. Submarine hunter: efficient and secure multi-type unmanned vehicles. Comput Mater Contin. 2023;76(1):573-589
IEEE Style
H.H. Mahmoud et al., "Submarine Hunter: Efficient and Secure Multi-Type Unmanned Vehicles," Comput. Mater. Contin., vol. 76, no. 1, pp. 573-589. 2023.

cc This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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