Past Work
Autonomous Platforms
ASSURE Small UAS Detect and Avoid Requirements Necessary for Limited Beyond Visual Line of Sight (BVLOS) Operations
The FAA sponsored this project within the ASSURE alliance. The projects’ partnership was led by RIAS (through the University of North Dakota) in partnership with New Mexico State University. The effort focused on:
- The identification of hazards related to the operation of UAS in Beyond-Visual-Line-of-Sight operations (BVLOS). Special attention was given to the assessment of the Radio-Line-of-Sight (RLOS) coverage.
- Development of a risk assessment that helps define requirements that ensure safe BVLOS operations.
ASSURE UAS Surveillance Criticality Final Report
Also under the ASSURE umbrella, partnership of this project extended to six leading UAS research universities (the UND among others). The project evaluated the impact of UAS Detect and Avoid (DAA) functions on current airborne surveillance technology performance. It made use of five different analysis tools: Fault Trees, Monte Carlo Simulations, Hazard Analysis, Design of Experiments (DOE) and Human-in-the-Loop Simulations.
ASSURE UAS Recommendations for Minimum UAS Control Station Standards and Guidelines
The objective of this project was to develop recommendations for minimum UAS operations and UAS control station standards and guidelines. UAS considered were fixed-wing and larger than 55 lb. Scenarios considered were BVLOS operations in an integrated National Airspace System (NAS).
Data Supply Chain and Cybersecurity
Cybersecurity Awareness and Research Symposium (CARS’18)
On October 18, 2018, RIAS organized the industry-led CARS’18 symposium to raise awareness about the importance of cybersecurity. It focused, among other aspects, on cybersecurity trends and engineering solutions to face today’s and tomorrow’s threats to UAS operations.
Next Generation Distributed and Networked Autonomous Vehicles
This paper provides a comprehensive survey of existing literature and futuristic road map in the design of autonomous systems. It was presented to the 2018 10th International Conference on Communication Systems & Networks, which took place in Bangalore, India in January 2018.
A Multi-Stage Price Forecasting Model for Day-Ahead Electricity Markets
This paper proposes a two-stage approach in predicting the electricity hourly spot prices. This novel approach is a combination of Auto-Regressive Integrated Moving Average (ARIMA) with other forecasting models.
Development of a GPS Spoofing Apparatus to Attack a DJI Matrie 100 Quadcopter
This paper details a step-by-step implementation of a low-cost GPS spoofing apparatus to model a simplistic spoofing attack. The results aim at better understanding spoofing technologies in order to successfully develop defensive mechanisms against them in the future.
A Review and Future Directions of UAV Swarm Communication Architectures
This paper presented a literature review on UAV swarm technology and proposed a swarm architecture over cellular mobile network infrastructure, which would allow for higher levels of autonomy and reliability.
Next Generation Counter-sUAS Swarm Technology
This project was focused on the development of UAS subsystems that would support autonomous flight missions in swarm environments. It analyzed aspects such as networking, simulation, flight logic, hardware, cybersecurity, power systems and computer vision.
Detecting False Data Injection Attack in mart Grids
This project analyzed the reliability of approaches such as Artificial Neural Networks (ANN) to detect potential falsified injected data on communications networks.
Investigation of a GPS Spoofing Attack
This project modeled a Global Positioning System (GPS) spoofing attack set-up on the L1 (civil) frequency, and investigated several defense mechanisms that use available open-source software and hardware.
Geo-Fence Detection System for UAV Airspace to Provide Counter-Autonomy
This project aimed at:
- Development of a swarm technology to deploy autonomous fleets of UAVs.
- Development of a heterogeneous sensor-based artificial intelligence for rogue drone detection.
Smart Grid Metering Infrastructures: Threats and Solutions
This project provided a comprehensive study on types of threats and solutions on smart grid communication and metering infrastructures. It also identified some recommended actions to minimize the effects of potential attacks.
Vehicular Cybersecurity Challenges
This project analyzed cyberattack types and security properties in vehicular networks in three hierarchical layers: sensing, communication and control. It took into account several challenges that hinder cybersecurity solutions, such as: limited external connectivity to the vehicle, limited computational performance and hazards to drivers and passengers lives.