Enhancing User Control on Personal Data Usage in Internet of Things Ecosystems

Abstract

Internet of Things (IoT) services are improving our life, supporting people in a variety of situations. However, due to the high volume of managed personal data, they can be a serious threat for individuals privacy. Users data are commonly gathered by devices scattered in the IoT, each of which sees a portion of them. The combination of different data may lead to infer users sensitive information. The distributed nature and the complexity of the IoT scenario cause users to lose the control on how their data are handled. In this paper, we start addressing this issue with a framework that empowers users to better control data management within IoT ecosystems. A novel privacy reference model allows users to state how their data can be processed and what cannot be inferred from them, and a dedicated mechanism allows enforcing the stated references. Experimental results show the efficiency of the enforcement.