Project 1: Improving GNSS Resiliency Using Edge AI Solutions
Investigators: Prof. Moussa Ayyash, Dr. Sufyan Almajali, Dr. Anand Singh, and Mr. Abedl-Rahman Almodawar
Summary: This project will leverage Edge Artificial Intelligence (Edge AI) to enhance the resilience of Global Navigation Satellite Systems (GNSS) in challenging environments. By deploying AI algorithms and models on edge devices, the project aims to reduce reliance on cloud infrastructures, particularly in dense blockage scenarios where GPS signals are weak or disrupted. The goal is to explore how bringing intelligence to the edge node can improve GNSS performance and resiliency in these difficult conditions.
This project aligns with CARNATIONS's mission of reducing transportation cybersecurity risks.
Project 2: Leveraging Generative Adversarial Networks for Enhanced Cybersecurity in Smart Transportation Systems
Investigators: Dr. Mohamed Rahouti (Fordham University), Prof. Moussa Ayyash (Chicago State University), and Mr. Ali Alfatemi (Fordham University)
Summary: The purpose of this collaborative project is to forge a transportation ecosystem that is not only intelligent and efficient but also inherently secure against an array of cyber threats. This project will utilize the capabilities of Generative Adversarial Networks (GANs) along with other generative AI methodologies to proactively identify, simulate, and neutralize cyber threats against sophisticated transportation networks. The project combines the strengths of GANs, Reinforcement Learning (RL), and differential privacy to significantly devise a cybersecurity framework for resilient and advanced transportation systems.
This project does not only align with CARNATIONS's mission of promoting secure and resilient navigation in advanced transportation systems but also sets a new benchmark for cybersecurity practices across the industry.