A New Similarity-Based Classification Scheme of Drone Network Attacks

The Internet of Drones (IoD) paradigm is an emerging technology that has gained significant attention from the research community in the recent years. Drone networks are now widely utilized across various sectors and industries. However, like all emerging technologies, these networks face numerous challenges with security being the most critical one. The wireless nature of drone communication makes them vulnerable to a range of cyber attacks. Additionally, the limited resources of drones pose challenges for implementing effective security solutions. In this paper, we propose a novel classification that categorizes various attacks on drone networks based on their similarities. The primary objective is to highlight the commonalities between different cyber attacks on drone systems. This classification will serve as the foundation for developing future unified solutions capable of efficiently mitigating multiple attack types simultaneously.

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Publication Details

Published
2024-12-04
DOI
https://doi.org/10.1109/csnet64211.2024.10851739
Citations
4
Primary Topic
Network Security and Intrusion Detection
Type
article
Field-Weighted Citation Impact
1.40
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article

A New Similarity-Based Classification Scheme of Drone Network Attacks

Atiq Ahmed, Guy Pujolle, Dominique Gaïti, Salah Dine Maham
4 citations
Network Security and Intrusion Detection
1.40
article

A New Similarity-Based Classification Scheme of Drone Network Attacks

Atiq Ahmed, Guy Pujolle, Dominique Gaïti, Salah Dine Maham
article en
4 citations

Abstract

The Internet of Drones (IoD) paradigm is an emerging technology that has gained significant attention from the research community in the recent years. Drone networks are now widely utilized across various sectors and industries. However, like all emerging technologies, these networks face numerous challenges with security being the most critical one. The wireless nature of drone communication makes them vulnerable to a range of cyber attacks. Additionally, the limited resources of drones pose challenges for implementing effective security solutions. In this paper, we propose a novel classification that categorizes various attacks on drone networks based on their similarities. The primary objective is to highlight the commonalities between different cyber attacks on drone systems. This classification will serve as the foundation for developing future unified solutions capable of efficiently mitigating multiple attack types simultaneously.

Centre National de la Recherche Scientifique (FR), Université de Technologie de Troyes (FR), Sorbonne Université (FR), LIP6 (FR)
Climate action
Openalex Percentile: Top 16%
Network Security and Intrusion Detection
1.40
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