A Privacy-Preserving Crowdsensing System with Muti-blockchain
Tao Peng, Jierong Liu, Jianer Chen, Guojun Wang · 2020
Mobile crowdsensing system has become a new paradigm application with popularity and development of smart mobile devices. It provides a costless and efficient model to collect sensory data. However, most of mobile crowdsensing systems are based on the centralized structure, which will lead to serious privacy disclosure. In this paper, we combine k-anonymity and blockchain to build a mobile corwdsensing system, in which the users can upload their sensory data and receive corresponding rewards without privacy disclosure concern. With the distributed structure system and encryption algorithm, the system achieves enhanced privacy preservation through breaking the link between data and rewards and their owners.