Security and Privacy in Mobile Crowdsourcing for Internet of Things

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Mobile crowdsourcing has emerged as a popular and effective method for data collection and processing in the Internet of Things (IoT) era. It is open to data owners to contribute their raw data collected by IoT devices to fulfill data intensive tasks or provide data-driven services, such as place (e.g., restaurant or hotel) recommendation or health condition monitoring. Some devices include sensors, vehicles, smart appliances, mobile devices and other sensor-rich devices. Mobile crowdsourcing, in recent years, has become an emerging business model to provide efficient data collection, as well as an efficient communication platform and computing system to deliver data services to a variety of data-driven applications, such as real-time traffic maps. This model is especially effective as it integrates the intelligence of a crowd (e.g., a public group and each member has IoT devices capable of sensing and computing) and the ubiquitous sensing of IoT devices. The contributed data from data owners are precisely selected with the purposes to solve the specific tasks or provide particular services efficiently and effectively. Compared with the traditional sensor networks, mobile crowdsourcing not only enhances local processing capability on collected data, but also enables the integration of semantically complex data with human intelligence. Unfortunately, despite the tremendous benefits of mobile crowdsourcing in IoT, it still faces many security, privacy and fairness challenges. The proposed research is envisioned to address these challenges, particularly by considering secure and privacy preserving decentralized data collection from IoT devices, which has not been considered in previously reported studies. In this research, our goal is to design a secure, privacy preserving and fair mobile crowdsourcing framework for data-driven IoT applications. Specifically, we will propose efficient and secure provenance schemes to guarantee reliability, accountability and trustworthiness of data sources in a satisfactory way, and design privacy preserving data collection and analysis schemes to prevent privacy leakage of data owners. In addition, we will develop blockchain based fair data exchange solutions to encourage data sharing for data owners. The proposed research will help Canada establish and reinforce its leadership in ICT (Information and Communication Technologies). As such, new business models and revenue streams can also be fostered and devised to ensure continued steady growth of the ICT sector in Canada. The proposed research focuses on the development and application of new technologies and solutions in the rapidly evolving field of IoT. The Highly Qualified Personnel (HQP) trained through the program will be equipped with security technologies, as well as wireless communications and mobile computing; these are crucial for success in today's era of IoT, and will help to ensure a prosperous future for the Canadian ICT industry.