<p>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 in various sectors and industries. However, like all emerging technologies, these networks face numerous challenges, with security being the most critical. The wireless nature of drone communication makes them vulnerable to a variety of cyber attacks. In addition, the limited resources of drones pose challenges in implementing effective security solutions. This paper proposes a new approach to classifying drone cyber-attacks based on their similarities. We introduce a new step-by-step framework model to classify cyber attacks. Then, we highlight the existence of commonalities between different cyber attacks that can occur in drone network systems. This classification will serve as the foundation for the development of future unified solutions capable of efficiently mitigating multiple attack types simultaneously.</p>

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A new similarity-based classification scheme of drone network attacks

  • Salah-Dine Maham,
  • Guy Pujolle,
  • Atiq Ahmed,
  • Dominique Gaiti

摘要

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 in various sectors and industries. However, like all emerging technologies, these networks face numerous challenges, with security being the most critical. The wireless nature of drone communication makes them vulnerable to a variety of cyber attacks. In addition, the limited resources of drones pose challenges in implementing effective security solutions. This paper proposes a new approach to classifying drone cyber-attacks based on their similarities. We introduce a new step-by-step framework model to classify cyber attacks. Then, we highlight the existence of commonalities between different cyber attacks that can occur in drone network systems. This classification will serve as the foundation for the development of future unified solutions capable of efficiently mitigating multiple attack types simultaneously.