Using Digital Twins as a Sandbox for the Evaluation of Cyber Attacks on Avionics Networks
Primary Investigator:
Mark Daniel Ward
Alisha Gadaginmath, Sanjana Gadaginmath, Yury A. Kuleshov, Hridhay Monangi (TA), Kabir Nagpal, Katie B. O’Daniel, Dalbert Sun, Lucas Tan, Korel Ucpinar, Nathan L. Veatch, Naren Velnambi
Abstract
Conventional methods of the evaluation of cyber attacks on avionics networks do not meet the requirements of the ongoing Industry 4.0 (I4.0) revolution. The proposed alternative method is the use of digital twins. Digital twins have not been widely used in avionics networks in academia. During the previous stages of research, the Purdue Data Mine students in collaboration with the Boeing Company mentors developed a prototype of a digital twin and simulated sample attacks. Based on the recent feedback from aviation industry experts, the research team is currently focused on increasing the fidelity of the digital twin and integrating the new attack vector related to Automatic Dependent Surveillance-Broadcast (ADS-B). The project goal is to design a digital twin-based avionics networks sandbox and validate its features with the new attack vector. Other students and industry researchers can potentially benefit from using the sandbox to evaluate cyber attacks on avionics networks.