Secure UAV Design

Instructor 

Dr. Md Tauhidur Rahman, Assistant Professor, Electrical and Computer Eng., Florida International University, Miami, Florida

Learning Objectives

The principal objective of this course is to educate and train undergraduate students and professionals in conducting thorough investigations of the attack surface and implementing measures to identify and mitigate potential security vulnerabilities present in the hardware and firmware/software utilized within Unmanned Aerial Vehicle (UAV) control systems.

Small Unmanned Aerial Vehicles (UAVs) or drones are receiving much attention in different sectors, including public services, emergency responses, and commercial usage, besides their military applications. However, such proliferation of UAVs has also increased their attack surfaces, ironically rendering them a potential safety threat to communities if compromised. In particular, these attacks have related to UAVs’ communication and software aspects, which has already produced significant research to mitigate such cyber attacks. Furthermore, hardware-based attacks have gained significant attention from the autonomous system community. This course provides a structured exploration of UAV technology, security threats, and emerging solutions.

• Unit 1: Introduction to UAV: this unit provides a comprehensive foundation on UAVs, covering their types, applications, and architectural components. It begins with an exploration of UAV classifications, distinguishing between fixed-wing, rotary-wing, and hybrid designs, as well as categorizing them based on size, range, and operational capabilities. The unit then delves into the diverse applications of UAVs across industries such as defense, agriculture, disaster management, and infrastructure inspection. Finally, it examines UAV architecture, detailing the essential hardware components (such as flight controller, sensors, and power sources), software frameworks for autonomous control, and communication links that enable real-time data transmission and remote operation. This unit equips learners with the fundamental knowledge required to understand and engage with UAV technologies.
• Unit 2: Hardware Security of UAV/Drones: this unit explores the critical vulnerabilities posed by hardware Trojans (HTs) in UAVs. It begins with an introduction to hardware Trojan threats specific to drones, detailing various attack vectors that can compromise UAV functionality, security, and reliability. Several variants of hardware Trojan attacks are introduced, showcasing different insertion techniques and their potential impact on UAV operations. The unit then progresses to the design and implementation of a hardware Trojan attack on a real drone, demonstrating practical exploitation methods. Additionally, detection mechanisms are discussed, with a focus on side-channel analysis as an effective tool for identifying malicious hardware modifications. This unit provides a comprehensive understanding of UAV hardware security, equipping learners with the knowledge to analyze, detect, and mitigate hardware Trojan threats in drone systems.
• Unit 3: UAV Cybersecurity: this unit provides an in-depth exploration of cybersecurity threats targeting UAV systems and operations. It begins with an overview of UAV architectures, their operational frameworks, and potential cyberattack vectors. A structured classification of cyberattacks is introduced, highlighting the diverse threats UAVs face in real-world scenarios. The unit then delves into specific attacks, including jamming attacks that disrupt UAV communications, denial-of-service (DoS) attacks on Wi-Fi-enabled UAVs, message injection and manipulation threats, GPS spoofing attacks that mislead navigation systems, and attacks on onboard sensors and critical control systems. Each attack type is analyzed alongside corresponding countermeasures, equipping learners with a comprehensive understanding of UAV cybersecurity challenges and defense strategies. This unit is essential for developing robust UAV security mechanisms against evolving cyber threats.
• Unit 4: Digital Twin of UAV: this unit introduces the concept of digital twins and their application in UAV systems, particularly in the context of hardware security research. It begins with an overview of digital twin technology, explaining how a high-fidelity virtual replica of a UAV can be created by integrating real-time data, machine learning models, and advanced simulations. The unit explores the process of building a UAV digital twin, highlighting its role in monitoring, testing, and enhancing UAV security. Additionally, it compares digital twins with traditional UAV simulations, emphasizing the advantages of real-time data synchronization, predictive analysis, and enhanced security testing. By leveraging digital twin technology, researchers can identify vulnerabilities, assess attack impacts, and develop more effective countermeasures without risking physical UAVs.
• Unit 5: Anti-Drone Systems: Components and Designs: This unit provides a comprehensive introduction to the critical need for anti-drone systems in response to the increasing security challenges posed by UAVs. It explores the risks of unauthorized drone activity, including airspace violations, industrial espionage, and criminal or terrorist threats. It delves into the core components of anti-drone technologies, covering detection methods such as radar, radio frequency (RF) detection, and electro-optical sensors and identification and neutralization strategies like RF jamming, GPS spoofing, and kinetic interception. Additionally, the module examines sensor fusion and the integration of AI-driven approaches to enhance anti-drone capabilities. By the end of this unit, learners will have a solid understanding of how modern counter-UAV systems operate and their role in protecting critical infrastructure, high-profile events, and restricted airspaces.

Prerequisites:

• A background in Digital Electronics, Embedded Systems, and Networking is desirable but not required.

Biography

Dr. Tauhidur Rahman is an Assistant Professor in the Department of Electrical and Computer Engineering at Florida International University (FIU). He obtained his Ph.D. in Computer Engineering from the University of Florida in 2017 (advised by Dr. Mark Tehranipoor). He is the recipient of NSF CRII and the director of the SeRLoP (Security, Reliability, Low-power, and Privacy) Research lab. His research interests include hardware security and trust, side-channel analysis, and embedded security. His research is funded by the National Science Foundation (NSF), the National Security Agency (NSA), the Department of Defense (DoD), and CyberFlorida.