Defuzzification: criteria and classification
Fuzzy Sets and Systems
A survey of trust and reputation systems for online service provision
Decision Support Systems
Proceedings of the 4th workshop on Embedded networked sensors
Reputation-based framework for high integrity sensor networks
ACM Transactions on Sensor Networks (TOSN)
Ear-phone: an end-to-end participatory urban noise mapping system
Proceedings of the 9th ACM/IEEE International Conference on Information Processing in Sensor Networks
Towards trustworthy participatory sensing
HotSec'09 Proceedings of the 4th USENIX conference on Hot topics in security
Location-based crowdsourcing: extending crowdsourcing to the real world
Proceedings of the 6th Nordic Conference on Human-Computer Interaction: Extending Boundaries
Crowd-sourced sensing and collaboration using twitter
WOWMOM '10 Proceedings of the 2010 IEEE International Symposium on A World of Wireless, Mobile and Multimedia Networks (WoWMoM)
YouProve: authenticity and fidelity in mobile sensing
Proceedings of the 9th ACM Conference on Embedded Networked Sensor Systems
Balancing accountability and privacy using e-cash (extended abstract)
SCN'06 Proceedings of the 5th international conference on Security and Cryptography for Networks
Recruitment framework for participatory sensing data collections
Pervasive'10 Proceedings of the 8th international conference on Pervasive Computing
Automatic image capturing and processing for PetrolWatch
ICON '11 Proceedings of the 2011 17th IEEE International Conference on Networks
A privacy-preserving reputation system for participatory sensing
LCN '12 Proceedings of the 2012 IEEE 37th Conference on Local Computer Networks (LCN 2012)
Quality Control in Crowdsourcing Systems: Issues and Directions
IEEE Internet Computing
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Social participatory sensing is a newly proposed paradigm that tries to address the limitations of participatory sensing by leveraging online social networks as an infrastructure. A critical issue in the success of this paradigm is to assure the trustworthiness of contributions provided by participants. In this paper, we propose an application-agnostic reputation framework for social participatory sensing systems. Our framework considers both the quality of contribution and the trustworthiness level of participant within the social network. These two aspects are then combined via a fuzzy inference system to arrive at a final trust rating for a contribution. A reputation score is also calculated for each participant as a resultant of the trust ratings assigned to him. We adopt the utilization of PageRank algorithm as the building block for our reputation module. Extensive simulations demonstrate the efficacy of our framework in achieving high overall trust and assigning accurate reputation scores.