About This Project
Drones are increasingly used in emergency response, delivery, wildfire management, and future air mobility. As these networks grow, systems must know which drones and communication nodes can be trusted. Our Texas A&M team is testing whether a context-aware cybersecurity service can improve UAS Traffic Management through authentication, telemetry monitoring, policy-based defense, and targeted encryption
Ask the Scientists
Join The DiscussionWhat is the context of this research?
Drone use is scaling from pilots into real operations, including delivery, emergency response, wildfire management, inspection, and future air mobility. A key shift is beyond visual line of sight (BVLOS) operation with the Federal Aviation Administration (FAA) and US DOT proposed rules to speed drone deployment.
Existing Unmanned Aircraft Systems (UAS) Traffic Management (UTM) research often focuses on route planning, conflict avoidance, and airspace separation. But cybersecurity research shows drone networks can also face spoofing, man-in-the-middle, command, and communication attacks.
Our project was inspired by that gap. Future UTM systems must know not only where drones are, but whether drones, operators, and communication nodes are legitimate and behaving safely. Our team’s paper tests a UTM cybersecurity service combining identity tracking, authentication, Security Information and Event Management (SIEM) monitoring, policy response, and targeted encryption.
What is the significance of this project?
Drone cybersecurity is becoming a public safety and logistics issue. Drone delivery is moving beyond pilots: Walmart and Wing are expanding to 100 additional stores, while Zipline has completed over 2 million commercial deliveries and raised more than $600M. Amazon has also aimed for 500M annual drone deliveries by 2030, as U.S. regulators move toward BVLOS rules that could speed commercial drone use.
As drones scale in delivery, emergency response, wildfire operations, medical delivery, and infrastructure inspection, systems must know which drones and communication nodes can be trusted. Our research focuses on that trust layer: not just where a drone is, but whether its identity, command path, and network behavior should be trusted.
Applications include secure drone communication for delivery networks, search-and-rescue, wildfire response, and medical delivery. This campaign helps move UAS cybersecurity toward a testbed and demo.
What are the goals of the project?
Our goal is to continue developing and demonstrating a cybersecurity service for UAS Traffic Management in a controlled testbed environment. The system is designed to help verify drone identity, monitor cyber-relevant events, and support safer responses when suspicious behavior is detected.
With this campaign, we aim to support a focused project phase: improving the testbed, refining a specific use case, and preparing a clear demonstration of trusted drone communication. The strongest demo directions currently under consideration are emergency response, wildfire and forestry operations, medical delivery, and autonomous flight testing.
By the end of this phase, we aim to better show how future drone networks can verify trusted participants, monitor suspicious behavior, and respond to cyber risks in realistic operating scenarios.
Budget
This campaign supports a focused next phase of our NASA University Student Research Challenge project. The funds will help us continue developing and demonstrating a drone cybersecurity testbed that can verify and track trusted drones and communication during UAS operations.
The drone hardware and networking equipment will support further testing of secure drone identification and security monitoring workflows. Replacement parts and lab support materials will help keep the physical drone testbed operational as we iterate. Demo and documentation materials will help us explain the research to public supporters, potential partners, and NASA USRC stakeholders.
As a part of our partnership with NASA, we will receive a $40k grant contingent on successfully crowdfunding $2000 from this campaign. We will use the funds from the grant to further purchase hardware to scale our testing setup and create tailored versions of the cybersecurity framework for different use cases.
Endorsed by
Project Timeline
This campaign will support the next phase of an ongoing NASA USRC research project. The team has already developed a technical foundation and completed initial lab testing. The next phase will focus on finalizing the funded use case, preparing the testbed, running additional authentication and monitoring tests, and sharing progress with backers through updates.
May 30, 2026
Begin crowdfunding campaign
Jun 05, 2026
High density drone simulations and logging capabilities demonstrated
Jun 10, 2026
Test bed drones and autopilot complete
Jun 20, 2026
Real telemetry data broadcast from drones
Jun 30, 2026
Ground sensing data
Meet the Team
Affiliates
Affiliates
Affiliates
Team Bio
We are a Texas A&M Global Cyber Research Institute (GCRI) Lab team led by Dr. Sandip Roy, with Dr. Jaewon Kim as advisor. We are working on a NASA University Student Research Challenge project focused on cybersecurity for Unmanned Aircraft Systems (UAS) Traffic Management. Our team has developed a technical paper and initial lab tests; this campaign supports the next testbed and demonstration phase.
Sean Hau Goh
Sean is a Computer Engineering student at Texas A&M University and the Fundraising Lead for this NASA USRC project. His role focuses on fundraising strategy, outreach, and translating our team’s UAS cybersecurity research into a clear story for supporters and partners.
Through the Meloy Engineering Entrepreneurship Program, he has worked on entrepreneurship, communication, content strategy, and outreach. He is using that experience to help connect this research to real-world use cases such as emergency response, wildfire management, medical delivery, and future drone traffic systems.
Jadon Lee
Jadon is currently leading the development and testing of the Security Information and Event Management (SIEM) software integration for the secure UTM framework. He is pursuing a bachelors in computer engineering at Texas A&M University.
Michael Ades
Michael Ades is a computer science graduate from Texas A&M University and will pursue his master’s degree at Carnegie Mellon University. For over a year, he has contributed to the development of secure drone technology, focusing on the attestation and authentication for the drone system.
Michael is a cybersecurity researcher who actively participates in Capture The Flag competitions, where he solves a wide range of security challenges mainly binary exploitation and reverse engineering. His work is motivated by the growing role of drones in field operations, logistics, and product delivery, and by the need to ensure these systems are secure and trustworthy.
He is also a co-author on research from this project that will be presented at the AIAA Conference in San Diego June 9th, 2026.
Email: [email protected] | [email protected]
Website: https://mikewiki.netlify.app/
Raymond Yang
Raymond is an undergraduate Computer Engineering student here at Texas A&M University and has worked on the hardware team. He is now leading the development of network segmentation integration within this project.
Claire Ku
Claire is pursuing her bachelors in electrical engineering at Texas A&M University and has worked on the hardware and building of the drones used. She is now leading in the development of ground sensors for this project.
Jaewon Kim, Ph.D.
Dr. Jaewon Kim received his Ph.D. degree in Computer Engineering from Texas A&M University and subsequently served as a Postdoctoral Associate in the Laboratory for Information and Decision Systems (LIDS) at the Massachusetts Institute of Technology (MIT). He currently serves as an Assistant Research Scientist at the Texas A&M Global Cyber Research Institute (GCRI). Dr. Kim directs an interdisciplinary research program dedicated to the security, resilience, and safe operation of next-generation cyber-physical systems (CPS) and autonomous infrastructures.
Dr. Kim's current research addresses critical real-time vulnerabilities through advanced dynamic watermarking methodologies and zero-trust architectures (ZTA). This work incorporates robust authentication and micro-segmentation to secure autonomous systems, including unmanned aerial and ground vehicles (UAVs/UGVs). Additionally, he investigates reinforcement learning applications to secure industrial control networks, multi-agent unmanned vehicles, and renewable energy distribution systems such as solar photovoltaic (PV) microgrids. His scholarly contributions are regularly featured in premier IEEE transactions and top-tier international conference proceedings.
In addition to his active scholarship, Dr. Kim contributes to the broader academic community as a workshop chair and lead investigator on multiple collaborative research initiatives. Committed to integrating rigorous theoretical principles with hands-on engineering applications, he prioritizes the mentorship of undergraduate and graduate researchers within his laboratory. Through this integrated approach, he is dedicated to establishing the structural frameworks required to build autonomous infrastructures that are Secure by Design and Resilient by Design.
website: https://sites.google.com/view/...
Additional Information
This project builds on research our team has already written up in a technical paper on cybersecurity for UAS Traffic Management. The paper describes a modular cybersecurity service with four main functions: authentication and authorization, security information and event management, policy-based cyber defense, and targeted encryption. Initial testing has focused on attestation, identity management, SIEM telemetry ingestion, and command-path validation in a lab testbed.
As drone delivery expands, future airspace may include a high quantity of drones moving packages, food, medicine, and other time-sensitive goods. Walmart and Wing are expanding drone delivery to hundreds of store locations, Zipline has completed over 2 million commercial deliveries, and companies like Amazon continue to pursue large-scale package delivery by drone.
Potential social benefit demos include:
Emergency response: Help test secure drone communication for scenarios where responders need to know which drones and network nodes are trusted. (Texas A&M Task Force 1)
Wildfire and forestry management: Explore how a secure UAS trust system could help distinguish authorized responder drones from unauthorized or risky drone activity. (Texas A&M Forest Service)
Medical delivery: Study how trusted drone identity and secure communication could support delivery of time-sensitive supplies.
Package and food delivery: Explore how high-volume drone delivery networks could verify trusted drones, detect suspicious behavior, and protect communication between drones, operators, and delivery infrastructure.
Additional Links: NASA USRC | Texas A&M Global Cyber Research Institute
Project Backers
- 1Backers
- 1%Funded
- $15Total Donations
- $15.00Average Donation
