The PhD course provides an overview to the Mobile CrowdSensing (MCS) paradigm with a specific focus to edge-based architectures and security mechanisms. The course is structured in three modules:
1. an introduction to the MCS paradigm, with an overview to some real-world experiments showing the challenges and opportunities of a collaborative approach for collecting information from the crowd.
2. a practical survey to some data analytics methodologies to optimize the design of MCS platform. This module will consider a standard MCS architecture and some possible enhancements in order to boost the performance. According to the skills of the students, this module might also be extended with a short hand-on session.
3. an overview of solutions and challenges in security and privacy for MCS. This module will expose the student to advanced techniques and best-practices to enforce security and privacy in MCS scenarios at both software and hardware levels. We will consider different attack strategies such as eavesdropping, data integrity manipulation and spoofing while discussing threats and solutions.
- Teacher: STEFANO CHESSA