Pyas: Pay for Your Aggregation Service—A Privacy Preserving Aggregation Protocol of Time-series Data
Author:
Publisher
Springer Science and Business Media LLC
Subject
Electrical and Electronic Engineering,Computer Science Applications
Link
https://link.springer.com/content/pdf/10.1007/s11277-023-10637-4.pdf
Reference25 articles.
1. Zhao, S., Li, F., Li, H., Lu, R., Ren, S., Bao, H., Lin, J. H., & Han, S. (2020). Smart and practical privacy-preserving data aggregation for fog-based smart grids. IEEE Transactions on Information Forensics and Security, 16, 521–536.
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3. Castelluccia, C., Chan, A. C., Mykletun, E., & Tsudik, G. (2009). Efficient and provably secure aggregation of encrypted data in wireless sensor networks. ACM Transactions on Sensor Networks (TOSN), 5(3), 20.
4. Liu, W. (2022). Privacy-preserving comparison based data aggregation protocols for mobile sensing. Peer-to-Peer Networking and Applications, 15(1), 549–558.
5. Han, S., Lin, J., Zhao, S., Xu, G., Ren, S., He, D., Wang, L., & Shi, L. (2020). Location privacy-preserving distance computation for spatial crowdsourcing. IEEE Internet of Things Journal, 7(8), 7550–7563.
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