ABSTRACT: Cyber-Physical Systems (CPS) have unique properties that can be exploited to design new privacy-enhancing technologies that minimize the negative impact to the utility of CPS. In this paper we show two examples of these properties.

The first example looks at how differential privacy degrades CPS performance due to the large noise addition, and we then show how the inherent noise of CPS can be leveraged to reduce the additional noise added by differential privacy algorithms, and therefore, minimize the negative impact on the system utility and safety. In the second example we look at the ability to sample at sensor readings on demand, and how this flexibility can be used to design adaptive sensor sampling algorithms that hide sensitive information without the need to add noise.

Jairo Giraldo received the B.S. degree in electronic engineering from the National University of Colombia, Manizales, in 2010, and the M.S. and Ph.D. degrees from the Universidad de los Andes, Bogot·, in 2012 and 2015, respectively. He is currently a Research Associate with the Computer Science Department, University of Texas at Dallas. His research interests include security and privacy of control systems and distributed control for the smart grid.

Alvaro Cardenas received the B.S. degree in electrical engineering with a minor in mathematics from the Universidad de los Andes, Bogot·, Colombia, in 2000, and the M.S. and Ph.D. degrees in electrical and computer engineering from the University of Maryland, College Park, MD, in 2002 and 2006, respectively. He is currently an Assistant Professor of Computer Science with the University of Texas at Dallas. His research interests include cyber-physical systems security and network security.

Murat Kantarcioglu received the B.S. degree in computer engineering from the Middle East Technical University (METU), Ankara, Turkey, in 2000, and the M.S. and Ph.D. degrees in computer science from Purdue University, West Lafayette, IN, in 2002 and 2005, respectively. He is a professor in the Computer Science Department and director of the UTD Data Security and Privacy Lab at the University of Texas at Dallas. His research focuses on creating technologies that can efficiently extract useful information from any data without sacrificing privacy or security.