As developers continue to build greater autonomy into cyber-physical systems (CPSs), such as unmanned aerial vehicles (UAVs) and automobiles, these systems aggregate data from an increasing number of sensors. However, more sensors not only create more data and more precise data, but they require a complex architecture to correctly transfer and process multiple data streams. This increase in complexity comes with additional challenges for functional verification and validation, a greater potential for faults, and a larger attack surface. What's more, CPSs often cannot distinguish faults from attacks. To address these challenges, researchers from the SEI and Georgia Tech collaborated on an effort to map the problem space and develop proposals for solving the challenges of increasing sensor data in CPSs. In this podcast from the Carnegie Mellon University Software Engineering Institute, Jerome Hugues, a principal researcher in the SEI Software Solutions Division, discusses this collaboration and its larger body of work, Safety Analysis and Fault Detection Isolation and Recovery (SAFIR) Synthesis for Time-Sensitive Cyber-Physical Systems.