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Colossal encipher isolation conserve classifier

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Registration ID: IJNRD_189654

Published ID: IJNRD2303487

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Abstract

One of the basic functions of this application is fully related to the agriculture farming and the yield fields. The main purpose of the project is how to rise classifying to the customers, such as fully holomorphic encryption. It supports a number of useful computations on cipher text in a broad range of applications, such as e-voting, private information retrieval, cloud security, and privacy protection. While FHE schemes do not require any interaction during computation. The key limitations are large cipher text expansion and inefficiency. Thus, to overcome these limitations, we develop a novel cryptographic tool, MAS-Encryption, to support real-value input and secure computation on the multiply-add structure. This application has related to the rise, yields and farming related empowerment to improve the crop cultivation yields by giving some ideas to the farmers. It will also give additional knowledge about the fertilizer and yields for the farmer needs. These data will be collected from the respective fields, and it may acquire from the right data set. The data will be stored in a chain like method for data security. The previous data set values will be added in the database in respective manner. They are not required for the additional value of the fertilizers as well as the yields data. Then all of rice’s data’s encryption format classify to the customers. We prove that the constructed classifiers are secure and evaluate their performance using real-world datasets. Experiments show that our proposed MASE scheme and MASE based classifiers are efficient, in the sense that we achieve an optimal trade-off between computation efficiency and communication interactions. Thus, we avoid the inefficiency of FHE based paradigm.

How To Cite (APA)

Supriya S & Pooja D (March-2023). Colossal encipher isolation conserve classifier. INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT, 8(3), e665-e668. https://ijnrd.org/papers/IJNRD2303487.pdf

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Paper Reg. ID: IJNRD_189654

Published Paper Id: IJNRD2303487

Research Area: Computer Science & Technology 

Author Type: Indian Author

Country: Chennai, Tamil Nadu, India

Published Paper PDF: https://ijnrd.org/papers/IJNRD2303487.pdf

Published Paper URL: https://ijnrd.org/viewpaperforall?paper=IJNRD2303487

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Call For Paper - Volume 10 | Issue 12 | December 2025

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