Crowdsourcing-based cooperative spectrum sensing (CCSS) refers to a spectrum-sensing service provider (SSP) outsourcing the spectrum-sensing tasks over a large geographic region to distributed mobile users referred to as mobile detectors. The promise and feasibility of CCSS are deeply rooted in the ubiquitous penetration of increasingly powerful mobile devices into everyday life and in the anticipated prevalence of dynamic spectrum access (DSA) in future mobile communication systems. CCSS is expected to be much more cost-effective than deploying a large-scale dedicated network of distributed spectrum sensors. This research is to investigate a secure and privacy-preserving CCSS architecture. The research tasks include: (1) incentive-aware and reputation-aware selection of mobile detectors whereby the SSP can select an optimal set of mobile detectors for a sensing task; (2) secure combination which enables the SSP to minimize the impact of false sensing reports on the final detection result; (3) a reputation system which records the past sensing performance of mobile detectors and provides crucial input into the selection of mobile detectors and the secure combination of sensing reports; and (4) spectrum-misuse detection to enable the realtime detection of unauthorized spectrum use.
This research will expand the fundamental understanding of security, privacy, and incentive issues in CCSS. Materials of this project will be made publicly available online as tutorials, talks, publications, and software toolkits. The education plan of this project is to develop new cross-disciplinary teaching materials on DSA and involve undergraduates, underrepresented students, and graduates in networking and security research.
