Attribute based Range Search over Encrypted Data for Privacy Preserving in Cloud Computing

Classification, which is commonly used task in data mining applications separates the data present in the database based on some category. For years and years, considering the rise of several privacy issues, solutions in the form of theoretical and practical have been proposed for the classification problem under various security models. However, for the late Notoriety about cloud computing, clients presently have the chance on outsource their data, clinched alongside encrypted form, and also those information mining assignments of the cloud.. The data on the cloud which is in encrypted form, therefore existing privacy preserving classification techniques are not applicable. In this paper, we focus on finding solution for the classification problem over the encrypted data .Users can store their data with encryption by the use of ordered relational data. So, the data is obtained correctly without decrypting.

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M-healthcare cloud computing system for multilevel and single handled privacy preserving cooperative authentication in patient diagnosis

10.24001/ijaems.icsesd2017.61 ◽

2017 ◽

Author(s):

Patil S.N ◽

Borkar B.S

Keyword(s):

Cloud Computing ◽

Computing System ◽

Privacy Preserving ◽

Patient Diagnosis ◽

Cloud Computing System

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Secure Ring Signature based privacy preserving of Public Auditing mechanism for outsourced data in cloud computing paradigm

Journal of Physics Conference Series ◽

10.1088/1742-6596/1916/1/012079 ◽

2021 ◽

Vol 1916 (1) ◽

pp. 012079

Author(s):

D Srivaishnavi ◽

T Arjun ◽

K Dhyaneshwaran ◽

R Deepak

Keyword(s):

Cloud Computing ◽

Privacy Preserving ◽

Ring Signature ◽

Public Auditing ◽

Computing Paradigm ◽

Outsourced Data

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Privacy-Preserving Deep Neural Network Methods: Computational and Perceptual Methods—An Overview

Electronics ◽

10.3390/electronics10111367 ◽

2021 ◽

Vol 10 (11) ◽

pp. 1367

Author(s):

Raghida El El Saj ◽

Ehsan Sedgh Sedgh Gooya ◽

Ayman Alfalou ◽

Mohamad Khalil

Keyword(s):

Neural Networks ◽

Classification Accuracy ◽

Deep Neural Networks ◽

Privacy Preserving ◽

Sensitive Data ◽

Encrypted Data ◽

High Classification Accuracy ◽

Hide Information ◽

Network Methods ◽

Cloud Environments

Privacy-preserving deep neural networks have become essential and have attracted the attention of many researchers due to the need to maintain the privacy and the confidentiality of personal and sensitive data. The importance of privacy-preserving networks has increased with the widespread use of neural networks as a service in unsecured cloud environments. Different methods have been proposed and developed to solve the privacy-preserving problem using deep neural networks on encrypted data. In this article, we reviewed some of the most relevant and well-known computational and perceptual image encryption methods. These methods as well as their results have been presented, compared, and the conditions of their use, the durability and robustness of some of them against attacks, have been discussed. Some of the mentioned methods have demonstrated an ability to hide information and make it difficult for adversaries to retrieve it while maintaining high classification accuracy. Based on the obtained results, it was suggested to develop and use some of the cited privacy-preserving methods in applications other than classification.

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