Date of Award


Document Type


Degree Name

Master of Science (MS)


Computer Engineering and Sciences

First Advisor

Marius Silaghi

Second Advisor

Hector Gutierrez

Third Advisor

Lucas Stephane

Fourth Advisor

Philip Bernhard


As the deployment and availability of robots grow rapidly, and spreads everywhere to reach places where they can communicate with humans, and they can constantly sense, watch, hear, process, and record all the environment around them, numerous new benefits and services can be provided, but at the same time, various types of privacy issues appear. Indeed, the use of robots that process data remotely causes privacy concerns. There are some main factors that could increase the capability of violating the users’ privacy, such as the robots’ appearance, perception, or navigation capability, as well as the lack of authentication, the lack of warning system, and the characteristics of the application. Here we analyze these factors and propose solutions that assist in mitigating the problem of privacy violation while using social robots. These solutions assist in solving the limitations of current robots and in producing privacy-sensitive robots. The result consists in usable, trusted, and comfortable techniques to bring security in the context of social robot utilization, to protect users’ privacy in the presence of social robots, to increase users’ awareness towards associated privacy risks, and to find trade-offs between privacy loss and utility achieved. The aim is to increase the user confidence in the privacy guarantees made available by the robots. The results are verified with surveys and experiment.