As a noteworthy business worldview, a few on-line information stages have developed to fulfill society's wants for individual explicit learning, any place a service provider assembles raw data from data givers, at that point offers data services to data clients. Notwithstanding, inside the data exchanging level, the data customers face a squeezing issue, i.e., an approach to confirm whether the service provider has actually gathered and handled data. During this paper, we propose TPDM, that effectively compose truthfulness and Privacy protection in data Markets. TPDM is structured inside in partner degree Encrypt-then-Sign way; utilize mostly homomorphism encryption and identity-based signature. It along encourage bunch confirmation, processing, and result check, though giving identity protection and data confidentiality. We used dataset and 2015 RECS dataset, severally. Our examination and investigation results that TPDM accomplishes numerous alluring properties, though obtaining low calculation and correspondence overheads once sustaining huge size data markets
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
customersupport@researchsolutions.com
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.