A robust Internet of Drones security surveillance communication network based on IOTA

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Abstract

Drones are increasingly utilized for a variety of purposes, spanning military to civilian applications. The rise in drone usage underscores privacy and security challenges concerning flight boundaries, data collection in public and private domains, as well as data storage and dissemination. Such issues highlight drones’ capability to communicate and securely store data over potentially insecure channels. Recognizing these challenges and gaps in the literature, this paper introduces an efficient and secure security surveillance model for the Internet of Drones (IoD). Our model ensures secure communication between Ground Stations (GS) and Drones, effectively addressing various attack types. Particularly, surveillance drones are vulnerable to physical capture attacks. We delve into a scenario where a network drone is physically apprehended. Leveraging the information stored within a drone, the attacker could potentially access the session. This paper proposes a solution to counter such threats. Through experiments using MATLAB and VScode, we evaluate our network's efficiency and scalability in relation to the surge in transactions. The findings reveal our model's prowess in handling large-scale networks. Specifically, when transactions surpass 1000 per minute, our model achieves approximately a 20% reduction in processing time compared to existing works. Moreover, our approach facilitates about 80% enhanced communication efficiency relative to the contemporary state-of-the-art frameworks. A security analysis through Automated Validation of Internet Security Protocols and Applications (AVISPA) further corroborates the robustness and security of our proposed communication strategy against diverse attack types.

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APA

Gilani, S. M., Anjum, A., Khan, A., Syed, M. H., Moqurrab, S. A., & Srivastava, G. (2024). A robust Internet of Drones security surveillance communication network based on IOTA. Internet of Things (Netherlands), 25. https://doi.org/10.1016/j.iot.2024.101066

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