Research Article
Detection of Targeted Attacks Using Medium-Interaction Honeypot for Unmanned Aerial Vehicle
@INPROCEEDINGS{10.1007/978-3-031-56583-0_11, author={Abdul Majid Jamil and Hassan Jalil Hadi and Sifan Li and Yue Cao and Naveed Ahmed and Faisal Bashir Hussain and Chakkaphong Suthaputchakun and Xinyuan Wang}, title={Detection of Targeted Attacks Using Medium-Interaction Honeypot for Unmanned Aerial Vehicle}, proceedings={Digital Forensics and Cyber Crime. 14th EAI International Conference, ICDF2C 2023, New York City, NY, USA, November 30, 2023, Proceedings, Part II}, proceedings_a={ICDF2C PART 2}, year={2024}, month={4}, keywords={Unmanned Aerial Vehicle Medium Interaction Honeypot Intrusion Detection System}, doi={10.1007/978-3-031-56583-0_11} }- Abdul Majid Jamil
Hassan Jalil Hadi
Sifan Li
Yue Cao
Naveed Ahmed
Faisal Bashir Hussain
Chakkaphong Suthaputchakun
Xinyuan Wang
Year: 2024
Detection of Targeted Attacks Using Medium-Interaction Honeypot for Unmanned Aerial Vehicle
ICDF2C PART 2
Springer
DOI: 10.1007/978-3-031-56583-0_11
Abstract
Over the last two decades, there has been significant growth in the drone industry with the emergence of Unmanned Aerial Vehicles (UAVs). Despite their affordability, the lack of security measures in commercial UAVs has led to numerous threats and vulnerabilities. In addition, software, and hardware complexity in UAVs also trigger privacy and security issues as well as cause critical challenges for government, industry and academia. Meanwhile, malicious activities have increased, including stealing confidential data from UAVs and hijacking UAVs. These attacks are not only illegitimate but also appear to be increasing in frequency and sophistication. In addition, the current defence mechanisms for counterattacks are not sustainable for two reasons: they either demand strict firmware updates for all of the system’s devices, or they demand the deployment of a variety of advanced hardware and software. This paper proposes a Medium Interaction Honeypot-Based Intrusion Detection System (MIHIDS) to protect UAVs. Our system assists in detecting active intruders in a specific range (radio frequency) and provides details of attacking technologies to exploit UAVs. Our system is a passive lightweight, signature-based MIHIDS that is simple to integrate into UAV without requiring changes in network configuration or replacement of current hardware or software. The performance assessment demonstrates that in a typical network situation, our proposed framework can identify MitM, Brute-force, and DE-authentication attacks with a maximum detection time of 60 s. Under normal network scenarios, a minimum True Positive Rate (TPR) and performance efficiency is 93% to 95% during a short-distance detector.
