The DOI matches its Crossref record; 28 of the 28 references it cites were found in a registry or an index.
A Blockchain Based Privacy-Preserving Incentive Mechanism in Crowdsensing Applications
Open accessAbstract
Crowdsensing applications utilize the pervasive smartphone users to collect large-scale sensing data efficiently. The quality of sensing data depends on the participation of highly skilled users. To motivate these skilled users to participate, they should receive enough rewards for compensating their resource consumption. Available incentive mechanisms mainly consider the truthfulness of the mechanism, but mostly ignore the issues of security and privacy caused by a “trustful” center. In this paper, we propose a privacy-preserving blockchain incentive mechanism in crowdsensing applications, in which a cryptocurrency built on blockchains is used as a secure incentive way. High quality contributors will get their payments that are recorded in transaction blocks. The miners will verify the transaction according to the sensing data assessment criteria published by the server. As the transaction information can disclose users’ privacy, a node cooperation verification approach is proposed to achieve$k$-anonymity privacy protection. Through theoretical analysis and simulation experiments, we show the feasibility and security of our incentive mechanism.
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Cites
Bitcoin: A Peer-to-Peer Electronic Cash System
Wright, C. S. (2008) · SSRN Electronic Journal · doi:10.2139/ssrn.3440802 · Cited by 13,922
k-ANONYMITY: A MODEL FOR PROTECTING PRIVACY
SWEENEY, L. (2002) · International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems · doi:10.1142/s0218488502001648 · Cited by 8,571
Douceur, J. R. (2002) · Lecture Notes in Computer Science · doi:10.1007/3-540-45748-8_24 · Cited by 4,419
Decentralizing Privacy: Using Blockchain to Protect Personal Data
Zyskind, G., Nathan, O., & Pentland, A. '. (2015) · 2015 IEEE Security and Privacy Workshops · doi:10.1109/spw.2015.27 · Cited by 2,617
Maximum Likelihood Estimation of Observer Error-Rates Using the EM Algorithm
Dawid, A. P., & Skene, A. M. (1979) · Applied Statistics · doi:10.2307/2346806 · Cited by 1,692
On the Security and Performance of Proof of Work Blockchains
Gervais, A., Karame, G. O., Wüst, K., Glykantzis, V., Ritzdorf, H., & Capkun, S. (2016) · Proceedings of the 2016 ACM SIGSAC Conference on Computer and Communications Security · doi:10.1145/2976749.2978341 · Cited by 1,646
Sprite: a simple, cheat-proof, credit-based system for mobile ad-hoc networks
Zhong, S., Chen, J., & Yang, Y. R. (2004) · IEEE INFOCOM 2003. Twenty-second Annual Joint Conference of the IEEE Computer and Communications Societies (IEEE Cat. No.03CH37428) · doi:10.1109/infcom.2003.1209220 · Cited by 1,219
Data Privacy through Optimal k-Anonymization
Bayardo, R. J., & Agrawal, R. (2005) · 21st International Conference on Data Engineering (ICDE'05) · doi:10.1109/icde.2005.42 · Cited by 1,131
Crowdsourcing to smartphones: incentive mechanism design for mobile phone sensing
Yang, D., Xue, G., Fang, X., & Tang, J. (2012) · Proceedings of the 18th annual international conference on Mobile computing and networking · doi:10.1145/2348543.2348567 · Cited by 997
Zerocoin: Anonymous Distributed E-Cash from Bitcoin
Miers, I., Garman, C., Green, M., & Rubin, A. D. (2013) · 2013 IEEE Symposium on Security and Privacy · doi:10.1109/sp.2013.34 · Cited by 983
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Applications of Blockchains in the Internet of Things: A Comprehensive Survey
Ali, M. S., Vecchio, M., Pincheira, M., Dolui, K., Antonelli, F., & Rehmani, M. H. (2019) · IEEE Communications Surveys & Tutorials · doi:10.1109/comst.2018.2886932 · Cited by 855
Blockchain Technologies for the Internet of Things: Research Issues and Challenges
Ferrag, M. A., Derdour, M., Mukherjee, M., Derhab, A., Maglaras, L., & Janicke, H. (2019) · IEEE Internet of Things Journal · doi:10.1109/jiot.2018.2882794 · Cited by 668
Towards secure and privacy-preserving data sharing in e-Health systems via consortium blockchain
Zhang, A., & Lin, X. (2018) · Journal of Medical Systems · doi:10.1007/s10916-018-0995-5 · Cited by 606
A Survey on Blockchain for Information Systems Management and Security
Berdik, D., Otoum, S., Schmidt, N., Porter, D., & Jararweh, Y. (2021) · Information Processing & Management · doi:10.1016/j.ipm.2020.102397 · Cited by 580
Habibzadeh, H., Nussbaum, B. H., Anjomshoa, F., Kantarci, B., & Soyata, T. (2019) · Sustainable Cities and Society · doi:10.1016/j.scs.2019.101660 · Cited by 303
Metadata
- Authors
- Wang, J., Li, M., He, Y., Li, H., Xiao, K., & Wang, C.
- Venue
- IEEE Access
- Published
- 2018
- Volume
- 6
- Pages
- 17545-17556
- ISSN
- 2169-3536 (ISSN-L)
- OpenAlex
- W2791307302
- Cited by
- 283
- References
- 28
- FWCI
- 48.24
- Type
- journal article
- Language
- en
- Open access
- gold
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- Wang, J., Li, M., He, Y., Li, H., Xiao, K., & Wang, C. (2018). A Blockchain Based Privacy-Preserving Incentive Mechanism in Crowdsensing Applications. IEEE Access. https://doi.org/10.1109/access.2018.2805837
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