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Journal of IoT in Social, Mobile, Analytics, and Cloud

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Design of Deep Learning Algorithm for IoT Application by Image based Recognition
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Analysis of Serverless Computing Techniques in Cloud Software Framework
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Review of Internet of Wearable Things and Healthcare based Computational Devices
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Stock Index Prediction with Financial News Sentiments and Technical Indicators
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Suspicious Human Activity Detection System
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ROBOT ASSISTED SENSING, CONTROL AND MANUFACTURE IN AUTOMOBILE INDUSTRY
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EFFICIENT RESOURCE ALLOCATION AND QOS ENHANCEMENTS OF IOT WITH FOG NETWORK
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Live Streaming Architectures for Video Data - A Review
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IoT Based Monitoring and Control System using Sensors
Volume-3 | Issue-2

Big Data Analytics for Improved Risk Management and Customer Segregation in Banking Applications
Volume-3 | Issue-3

A Novel Signal Processing Based Driver Drowsiness Detection System
Volume-3 | Issue-3

IoT BASED AIR AND SOUND POLLUTION MONITIORING SYSTEM USING MACHINE LEARNING ALGORITHMS
Volume-2 | Issue-1

Analysis of Serverless Computing Techniques in Cloud Software Framework
Volume-3 | Issue-3

Hybrid Intrusion Detection System for Internet of Things (IoT)
Volume-2 | Issue-4

Home / Archives / Volume-4 / Issue-2 / Article-1

Volume - 4 | Issue - 2 | june 2022

Review on Advanced Cost Effective Approach for Privacy with Dataset in Cloud Storage
Vijesh Joe 
Pages: 73-83
Cite this article
Joe, V. (2022). Review on Advanced Cost Effective Approach for Privacy with Dataset in Cloud Storage. Journal of IoT in Social, Mobile, Analytics, and Cloud, 4(2), 73-83. doi:10.36548/jismac.2022.2.001
Published
13 July, 2022
Abstract

Cloud computing allows customers to run compute and data-intensive applications without the need for a large investment in infrastructure. Additionally, a significant amount of intermediate datasets are created and often saved, in order to reduce the expense of re-computing these applications. It becomes difficult to protect the privacy of intermediate datasets because attackers may be able to retrieve information that is sensitive to privacy via the analysis of several intermediate datasets. Existing techniques to deal with this problem generally endorse the use of encryption for all cloud datasets. For data-intensive applications, the time and expense of repeatedly decrypting and encrypting intermediate datasets are prohibitive; hence, encrypting all intermediate datasets does not make sense. Big heterogeneous data storage concerns and challenges, countermeasures (security and administration) and cloud storage prospects, are discussed in this article. New questions arise for cloud storage researchers, when they examine these issues in depth.

Keywords

Privacy in cloud cloud storage authentication data security data protection homomorphic encryption

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