This paper addresses the challenge of measuring security, understood as a system property, of cyberphysical systems, in the category of similar properties, such as safety and reliability. First, it attempts to define precisely what security, as a system property, really is. Then, an application context is presented, in terms of an attack surface in cyberphysical systems. Contemporary approaches related to the principles of measuring software properties are also discussed, with emphasis on building models. These concepts are illustrated in several case studies, based on previous work of the authors, to conduct experimental security measurements.

While students are often passionate about their chosen fields, they often have limited awareness of the profound impact of AI technologies on their professions. In order to advance efforts in building subject-relevant AI literacy among undergraduate students studying Computer Science and non-Computer Science (Criminal Justice and Forensic Science) it is imperative to engage in rigorous efforts to develop and study curricular infusion of Artificial Intelligence topics. Using a Design-Based Research model, the project team and the external evaluators studied the first iteration of the module development and implementation. Using data collected through surveys, focus groups, critical review, and reflection exercises the external evaluation team produced findings that informed the project team in revising and improving their materials and approach for the second iteration. These efforts can help educators and the AI module developers tailor their AI curriculum to address these specific areas, ensuring that students develop a more accurate understanding of applications of AI in their future career field.