Achieving Data Truthfulness and Privacy Preservation in Data Markets over Cloud Computing

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Siddavatam Lakshmi Datta Meghana


As data plays an important role in any organization where data DE duplication is a data encoding approach which is used for deleting present duplicate copies of replicated data, as well as it is preferably used for storage purpose in cloud to conserve space and bandwidth. To preserve privacy laws with some allowing de-duplication, the heterogeneous encoding method has been proposed to secure communications before privatization. It is the first comprehensive effort to address the issue of permitted data de-duplication in addition to enhancing data security. In contrast to conventional de-duplication methods, the replicate check approach often discusses both the data and the users' differential rights. In a hybrid cloud architecture, we do demonstrate a number of new de-duplication structures that allow for duplicate check. Our scheme is secure in respect of the definitions identified in the proposed security model, thus according securing data. We provide a prototype of our proposed accepted duplicate check scheme as a proof of concept and perform experiments with it. As compared to conventional operations, we display that our proposed allowed replicate check schemes suffers reduced overlap.


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Siddavatam Lakshmi Datta Meghana. (2021). Achieving Data Truthfulness and Privacy Preservation in Data Markets over Cloud Computing. Turkish Journal of Computer and Mathematics Education (TURCOMAT), 12(13), 56–61.
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