Publication on privacy control to support smart city data exchanges

As cities move toward “smart city” paradigms they will engage more and more with private mobility operators. Examples of these efforts include the Mobility Data Specification from LA DOT. Data sharing for such ecosystems require mechanisms to preserve the competitive privacy of operators’ operational policies. In our latest paper, we develop one such mechanism using concepts of constrained entropy maximization and inverse optimization constraints to ensure synthetic queries exhibit certain desirable features. This work will be presented at ISTTT23 in Lausanne and is funded by NSF CMMI-1652735

Link to paper: https://www.sciencedirect.com/science/article/pii/S0968090X1831622X