The key to realizing the smart functionalities envisioned through the Internet of Things (IoT) is to securely and efficiently communicate, store, and make sense of the tremendous data generated by IoT devices. Therefore, integrating IoT with the cloud platform for its computing and big data analysis capabilities becomes increasingly important, since IoT devices are computational units with strict performance and energy constraints. However, when data is transferred among interconnected devices or to the cloud, new security and privacy issues arise. In this project, we investigate the privacy threats in the cloud-assisted IoT systems, in which heterogeneous and distributed data are collected, integrated and analyzed by different IoT applications. The goal of the project is to develop a privacy threat analysis framework to provide a systematic methodology for modeling privacy threats in the cloud-assisted IoT systems.

Successful completion of this project will result in: (i) a systematic methodology to model privacy threats in data communication, storage, and analysis processes in the cloud-assisted IoT systems; (ii) a privacy threats analysis framework with extensive catalogue of application-specific privacy needs and privacy-specific threat categorization; and (iii) a privacy protection framework that maps existing privacy enhancing technologies (PETs) to the identified privacy needs and threats of IoT applications to simplify the selection of sound privacy protection countermeasures.