The goal of this proposal is to establish a framework for cascading failure abstraction and vulnerability analysis in Cyber-Physical Systems (CPSs), empowered by data. CPSs are critical to modern society, however, they are vulnerable to attacks and failures. The failures in CPSs are more destructive because of cascading failure, which means that the failure of a part of the system can cause failure in the rest of the system and result in more severe damage. However, analysis of CPS vulnerability involving cascading failure is extremely challenging, mainly because 1) it?s hard to theoretically analyze the various physical processes happen in a cascade and 2) local diffusion models applied to the CPS network cannot capture the global impact of cascades. Using simpler cascade models derived from data as media, it is possible to have a deeper understanding of how CPSs are vulnerable to cascading failure. CPSs are gaining popularity and there is an urgent need to enhance its security, hence the proposed work will greatly benefit the society and of national interest. The project will provide opportunities for undergraduate students, underrepresented minority groups and women to research in some of the society's most concerned fields like machine learning and security. Also, the outcomes of this work will be introduced in courses for undergraduate and graduate students and integrated into STEM outreach programs for K-12 students.