Analysis of IoT Privacy Policies in Smart Transportation Systems

Smart transportation systems utilize a variety of Internet of Things (IoT) sensors, real-time data communication technologies, and advanced computing techniques to manage its services, resources, and infrastructure more efficiently. There is an increasing interest in transforming transportation systems into intelligent systems, but persistent concerns over privacy are slowing down the adoption of smart applications. This paper presents a knowledge elicitation methodology based on natural language processing and deep learning techniques to analyze privacy policies of several smart transportation IoT applications. Text similarity analysis is performed to identify the privacy functions that are less frequently addressed by IoT privacy policies. Initial results support decision-makers in understanding the contextual privacy characteristics of the smart transportation domain.