The integration and digital connection of National Airspace System (NAS) with Unmanned Aircraft Systems (UAS) and Advanced Air Mobility (AAM) provides more pathways for hackers to attack the aircrafts. To address this critical challenge, University Technical Services, Inc. (UTS) proposes to develop an onboard noninvasive intrusion detection system (ONRIDE). The key innovation in this work is the development of traffic-flow analysis techniques and machine learning-based anomaly detection algorithms to achieve efficient and effective cyber threat detection, analysis and mitigation. The proposed technology, if successful, will achieve a breakthrough in the computational efficiency for onboard and noninvasive cybersecurity assessment and risk analysis of aircrafts as well as the space segments in the NAS. ONRIDE can monitor and analyze aviation data bus traffic in real time and detect if there is a threat. Potential NASA Applications (Limit 1500 characters, approximately 150 words): The proposed technology addresses a critical need in NASAs strategic goals to advance the state-of-the-art in the autonomous flight operations and onboard cyber/system security. Within NASA, the Unmanned Aircraft Systems (UAS) in the National Airspace System (NAS) (UAS-NAS) Project, the Advanced Air Mobility (AAM) project, and the System-Wide Safety (SWS) project will be directly benefit from ONRIDE. Potential Non-NASA Applications (Limit 1500 characters, approximately 150 words): Has uses for satellite communications, network on-the-move, swarm drone/robotic networks, and UAVs. The proposed technology can be directly applied to the Urban Air Mobility (UAM) systems. Duration: 6
