Abstract
To address the challenges of privacy preserving and incentive mechanisms, the paper proposes a system and a strategy to ensure anonymous data reporting while ensuring incentives simultaneously. The envisioned system model consists of four main entities: service provider, data collector, credit authority and participants, which interact through a specific protocol. The proposed protocol is arranged in five stages that mainly leverage three concepts: (1) slot reservation based on shuffle, (2) data submission based on bulk transfer and multi-player dc-nets, and (3) incentive mechanism based on blind signature. Slot reservation aims to establish a submission schedule by anonymously assigning a slot in a vector to each member in a group of participants. The assigned slot is distributed in a fashion where every member and system entities are oblivious of other members’ slots. Similarly, bulk transfer (data submission) allows group members to transmit encoded data to service provider within their reserved slots in an encoded vector. Service provider then combines members’ vectors to get the data without ability to link any data to a specific member and thus, reporting anonymity is preserved. Finally, blind signature ensures the incentive mechanism via anonymous micro-payments transferred by the help of the Credit authority. Theoretical analysis of the protocol is conducted, proving the integrity, anonymity and efficiency of the protocol. We implemented and tested the protocol on Android phones. Experimental results shows that the protocol is efficient for high latency application which is the case for most of crowd-sensing applications. The results shows also the advantage of our optimization over similar anonymous data reporting protocol.
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Acknowledgements
This research was supported by Harbin Scientific and Technological Achievement Transformation Project under Grant No. 2014DB1AG022, The Youth Foundation of Heilongjiang Province of China under Grant No. QC2016083, and The Fundamental Research Funds for the Central Universities under Grant No. HEUCF160612.
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Li, Y., Zhao, Y., Ishak, S. et al. An anonymous data reporting strategy with ensuring incentives for mobile crowd-sensing. J Ambient Intell Human Comput 9, 2093–2107 (2018). https://doi.org/10.1007/s12652-017-0529-x
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DOI: https://doi.org/10.1007/s12652-017-0529-x