Theme Article: Special Section on Security and Sustainability Technologies for Smart Cities Technologies Reverse Engineering Controller Area Network Messages Using Unsupervised Machine Learning Uchenna Ezeobi University of Colorado at Colorado Springs Habeeb Olufowobi The University of Texas at Arlington Clinton Young Iowa State University Joseph Zambreno Iowa State University Gedare Bloom University of Colorado at Colorado Springs Abstract-The smart city landscape is rife with opportunities for mobility and economic optimization, but also presents many security concerns spanning the range of components and systems in the smart ecosystem. One key enabler for this ecosystem is smart transportation and transit, which is foundationally built upon connected vehicles. Ensuring vehicular security, while necessary to guarantee passenger and pedestrian safety, is itself challenging due to the broad attack surfaces of modern automotive systems. A single car contains dozens to hundreds of small embedded computing devices known as electronic control units (ECUs) executing hundreds of millions of lines of code; the inherent complexity of this tightly integrated cyber-physical system (CPS) is one of the key problems that frustrate effective security. We describe an approach to help reduce the Digital Object Identifier 10.1109/MCE.2020.3023538 Date ofpublication 11 September 2020; date ofcurrent version 6 December 2021. 50 2162-2248 ß 2020 IEEE Published by the IEEE Consumer Technology Society IEEE Consumer Electronics Magazine