Designing Privacy Aware Internet of Things Applications.

Abstract

The Internet of Things (IoT) integrates physical devices with software, enabling extensive data interactions. This combination, often involving diverse specialists, leads to complexity, with privacy often overlooked. Given the sensitive nature of data in many IoT applications and the strict privacy regulations they face, early privacy consideration is essential. Many researchers advocate techno-regulatory methods like privacy-by-design (PbD) principles. Their complexity and lack of clear guidelines make their application in IoT challenging. We present a simplified and visual method for IoT developers to embed privacy into their applications. Unlike traditional methodologies that involve complex and time-consuming steps, our method is straightforward and interactive. Our framework approach is intended for the conceptual design phase of the software development life cycle (SDLC) to support early dialogue between lawyers and developers in the context of IoT app design. The key value is following a user(developer)-centric approach to fulfil their needs in addition to meeting privacy requirements. The thesis contributes in three ways. First, by exploring non-IoT privacy techniques, we discovered the challenges of migrating these strategies to IoT. Second, our subsequent interactions with developers and privacy experts revealed common challenges in privacy design. Accordingly, we proposed PARROT (PrivAcy by design tool foR inteRnet Of Things), a tool engineered to intuitively guide IoT developers. Third, our exploration of less regulated domains illustrated further privacy challenges and underscored the potential of tools like PARROT to amplify awareness of privacy norms in IoT design. Through multiple case studies and experiments, we validated PARROT’s effectiveness in reducing privacy issues while designing IoT applications. Overall, the experimental results demonstrated in this thesis confirm our hypothesis that PARROT reduces privacy mistakes and increases privacy knowledge among developers during the Internet of Things software design phase by offering an interactive design method to augment the design process and provide real-time feedback.