2023/12/28 by Yejun Kim, Kim, Yejun, Kwang‐Soo Cho +3 · 1 citation
Computer Science · Engineering · #Advanced Malware Detection Techniques #Cryptography and Security (cs.CR) #FOS: Computer and information sciences #Opportunistic and Delay-Tolerant Networks #Robotics (cs.RO) #UAV Applications and Optimization
paper · pdf · doi:10.48550/arxiv.2312.16818
openalex publication_date 2023/12/28 · openalex created_date 2023/12/30 · openalex updated_date 2026/07/28
With the advancement of Internet of Things (IoT) technology, its applications span various sectors such as public, industrial, private and military. In particular, the drone sector has gained significant attention for both commercial and military purposes. As a result, there has been a surge in research focused on vulnerability analysis of drones. However, most security research to mitigate threats to IoT devices has focused primarily on networks, firmware and mobile applications. Of these, the use of fuzzing to analyze the security of firmware requires emulation of the firmware. However, when it comes to drone firmware, the industry lacks emulation and automated fuzzing tools. This is largely due to challenges such as limited input interfaces, firmware encryption and signatures. While it may be tempting to assume that existing emulators and automated analyzers for IoT devices can be applied to drones, practical applications have proven otherwise. In this paper, we discuss the challenges of dynamically analyzing drone firmware and propose potential solutions. In addition, we demonstrate the effectiveness of our methodology by applying it to DJI drones, which have the largest market share.