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Unmanned Aerial Vehicles (UAVs) are increasingly used in military operations, disaster management, and urban planning. Nevertheless, its susceptibility to cyber-attacks has generated substantial cybersecurity apprehensions. The UAVCAN protocol, widely employed for UAV communication, is vulnerable to sophisticated threats such as message spoofing, replay, and Denial of Service (DoS) assaults. This research presents an Intrusion Detection System (IDS) that uses deep reinforcement learning to safeguard UAVCAN networks against cyber threats. The suggested IDS utilizes artificial intelligence (AI) techniques to safeguard against emerging attack patterns. These systems provide robust defense mechanisms specifically designed to address the distinct problems UAVCAN offers. The system’s detection accuracy has been extensively validated through experiments, showing remarkable performance in identifying various attack situations. This dramatically improves the cybersecurity and resilience of UAV communication networks. This study focuses on specific IDS requirements in UAVs. This solution presented in the study makes a valuable contribution to the field of UAV cybersecurity by effectively and promptly addressing sophisticated cyber-attacks.

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Cybersecurity in UAVs: An Intrusion Detection System Using UAVCAN and Deep Reinforcement Learning

  • 会议论文

  • 发表日期：

    2025年

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  • Md Rezanur Islam,
  • Kamronbek Yusupov,
  • Ibrokhim Muminov,
  • Mahdi Sahlabadi,
  • Kangbin Yim

摘要

Unmanned Aerial Vehicles (UAVs) are increasingly used in military operations, disaster management, and urban planning. Nevertheless, its susceptibility to cyber-attacks has generated substantial cybersecurity apprehensions. The UAVCAN protocol, widely employed for UAV communication, is vulnerable to sophisticated threats such as message spoofing, replay, and Denial of Service (DoS) assaults. This research presents an Intrusion Detection System (IDS) that uses deep reinforcement learning to safeguard UAVCAN networks against cyber threats. The suggested IDS utilizes artificial intelligence (AI) techniques to safeguard against emerging attack patterns. These systems provide robust defense mechanisms specifically designed to address the distinct problems UAVCAN offers. The system’s detection accuracy has been extensively validated through experiments, showing remarkable performance in identifying various attack situations. This dramatically improves the cybersecurity and resilience of UAV communication networks. This study focuses on specific IDS requirements in UAVs. This solution presented in the study makes a valuable contribution to the field of UAV cybersecurity by effectively and promptly addressing sophisticated cyber-attacks.