Reverse Engineering and Control-Aware Security Analysis of the ArduPilot UAV Framework
- URL: http://arxiv.org/abs/2512.01164v1
- Date: Mon, 01 Dec 2025 00:47:11 GMT
- Title: Reverse Engineering and Control-Aware Security Analysis of the ArduPilot UAV Framework
- Authors: Yasaswini Konapalli, Lotfi Ben Othmane, Cihan Tunc, Feras Benchellal, Likhita Mudagere,
- Abstract summary: ArduPilot is among the most widely used open-source autopilot UAV frameworks.<n>This paper reconstructs the software architecture and the control models implemented by ArduPilot.<n>We examine how these control models could potentially misused to induce malicious behaviors while relying on legitimate inputs.
- Score: 0.2609784101826761
- License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
- Abstract: Unmanned Aerial Vehicle (UAV) technologies are gaining high interest for many domains, which makes UAV security of utmost importance. ArduPilot is among the most widely used open-source autopilot UAV frameworks; yet, many studies demonstrate the vulnerabilities affecting such systems. Vulnerabilities within its communication subsystems (including WiFi, telemetry, or GPS) expose critical entry points, and vulnerabilities in Ardupilot can affect the control procedure. In this paper, we reconstruct the software architecture and the control models implemented by ArduPilot and then examine how these control models could potentially misused to induce malicious behaviors while relying on legitimate inputs.
Related papers
- A Compendium of Autonomous Navigation using Object Detection and Tracking in Unmanned Aerial Vehicles [0.0]
Unmanned Aerial Vehicles (UAVs) are one of the most revolutionary inventions of 21st century.<n>This paper attempts to review the various approaches several authors have proposed for the purpose of autonomous navigation of UAVs.
arXiv Detail & Related papers (2025-05-31T09:13:43Z) - Behind The Wings: The Case of Reverse Engineering and Drone Hijacking in DJI Enhanced Wi-Fi Protocol [0.5604521993453262]
Investigation discovered vulnerabilities in the Enhanced Wi-Fi control commands, rendering them susceptible to hijacking attacks.
Study established that even readily available and cost-effective commercial off-the-shelf Wi-Fi routers could be leveraged as effective tools for executing such attacks.
Findings emphasize the critical necessity of implementing robust security measures to safeguard unmanned aerial vehicles.
arXiv Detail & Related papers (2023-09-12T02:03:27Z) - Convergence of Communications, Control, and Machine Learning for Secure
and Autonomous Vehicle Navigation [78.60496411542549]
Connected and autonomous vehicles (CAVs) can reduce human errors in traffic accidents, increase road efficiency, and execute various tasks. Reaping these benefits requires CAVs to autonomously navigate to target destinations.
This article proposes solutions using the convergence of communication theory, control theory, and machine learning to enable effective and secure CAV navigation.
arXiv Detail & Related papers (2023-07-05T21:38:36Z) - Evidential Detection and Tracking Collaboration: New Problem, Benchmark
and Algorithm for Robust Anti-UAV System [56.51247807483176]
Unmanned Aerial Vehicles (UAVs) have been widely used in many areas, including transportation, surveillance, and military.
Previous works have simplified such an anti-UAV task as a tracking problem, where prior information of UAVs is always provided.
In this paper, we first formulate a new and practical anti-UAV problem featuring the UAVs perception in complex scenes without prior UAVs information.
arXiv Detail & Related papers (2023-06-27T19:30:23Z) - VBSF-TLD: Validation-Based Approach for Soft Computing-Inspired Transfer
Learning in Drone Detection [0.0]
This paper presents a transfer-based drone detection scheme, which forms an integral part of a computer vision-based module.
By harnessing the knowledge of pre-trained models from a related domain, transfer learning enables improved results even with limited training data.
Notably, the scheme's effectiveness is highlighted by its IOU-based validation results.
arXiv Detail & Related papers (2023-06-11T22:30:23Z) - ADAPT: An Open-Source sUAS Payload for Real-Time Disaster Prediction and
Response with AI [55.41644538483948]
Small unmanned aircraft systems (sUAS) are becoming prominent components of many humanitarian assistance and disaster response operations.
We have developed the free and open-source ADAPT multi-mission payload for deploying real-time AI and computer vision onboard a sUAS.
We demonstrate the example mission of real-time, in-flight ice segmentation to monitor river ice state and provide timely predictions of catastrophic flooding events.
arXiv Detail & Related papers (2022-01-25T14:51:19Z) - DAE : Discriminatory Auto-Encoder for multivariate time-series anomaly
detection in air transportation [68.8204255655161]
We propose a novel anomaly detection model called Discriminatory Auto-Encoder (DAE)
It uses the baseline of a regular LSTM-based auto-encoder but with several decoders, each getting data of a specific flight phase.
Results show that the DAE achieves better results in both accuracy and speed of detection.
arXiv Detail & Related papers (2021-09-08T14:07:55Z) - Anti-UAV: A Large Multi-Modal Benchmark for UAV Tracking [59.06167734555191]
Unmanned Aerial Vehicle (UAV) offers lots of applications in both commerce and recreation.
We consider the task of tracking UAVs, providing rich information such as location and trajectory.
We propose a dataset, Anti-UAV, with more than 300 video pairs containing over 580k manually annotated bounding boxes.
arXiv Detail & Related papers (2021-01-21T07:00:15Z) - Artificial Intelligence for UAV-enabled Wireless Networks: A Survey [72.10851256475742]
Unmanned aerial vehicles (UAVs) are considered as one of the promising technologies for the next-generation wireless communication networks.
Artificial intelligence (AI) is growing rapidly nowadays and has been very successful.
We provide a comprehensive overview of some potential applications of AI in UAV-based networks.
arXiv Detail & Related papers (2020-09-24T07:11:31Z) - Consumer UAV Cybersecurity Vulnerability Assessment Using Fuzzing Tests [0.0]
Unmanned Aerial Vehicles (UAVs) are remote-controlled vehicles capable of flight.
Cyber attacks on UAVs can bring a plethora of issues to physical and virtual systems.
To mitigate such attacks, it is necessary to identify and patch vulnerabilities.
arXiv Detail & Related papers (2020-08-09T00:40:54Z) - Target Detection, Tracking and Avoidance System for Low-cost UAVs using
AI-Based Approaches [1.5836913530330785]
An onboard target detection, tracking and avoidance system has been developed for low-cost UAV flight controllers using AI-Based approaches.
The proposed system is that an ally UAV can either avoid or track an unexpected enemy UAV with a net to protect itself.
arXiv Detail & Related papers (2020-02-27T21:58:54Z)
This list is automatically generated from the titles and abstracts of the papers in this site.
This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.