Excellence in Research: Towards Secure Unmanned Aerial Vehicles-based Systems

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This project aims to enhance the resilience of deep learning-based Unmanned Aerial Vehicles (UAV) navigation systems to novel attack vectors that attempt to misguide the UAV by making small changes to the sensed data. Such systems are vulnerable to different attacks, which can result in the misguidance or hacking of the UAV, posing significant safety risks. Different types of adversarial attacks will be considered. Additionally, the project will investigate defense methods against these types of stealthy attacks using state-of-the-art methods as well as experimentations. The performance of the models will be judged according to their ability to resist attacks through simulations and real-world experiments using a UAV testbed. The results of this research will have significant implications for the development of safe and reliable UAV navigation systems, with potential applications in various fields such as crop monitoring, search and rescue, and infrastructure inspection. The project aligns with NSF's mission to promote fundamental research, advance the national interest, and contribute to the broader scientific community by sharing its findings through publications and open-source software. The research will support technical development and engagement of underrepresented graduate and undergraduate students at North Carolina A&T State University. The funding will also enhance development of undergraduate/graduate-level course modules and certificates in autonomy.The project will investigate attack scenarios that combine two triggers, namely trojan and adversarial triggers, to create a malign behavior where the model remains robust in the absence of a trojan under adversarial attacks but behaves maliciously when the trojan is present. To address these attacks, a deep learning-based detection model will be developed that learns features from both adversarial perturbations and counterfactual attributions, to detect and mitigate these attacks. Secure deployment will also be investigated, including remote controller and secure hardware.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.