Privacy Preserving and Public Auditing Service for Data Storage in Cloud Computing

Tejaswini, V.; Sunitha, K.; Prashanth, S. K.

doi:10.15373/22501991/feb2013/44

Cited by 10 publications

(2 citation statements)

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“…Allows data power, but does not guarantee that data stored in the cloud is secure. To establish data integrity through TPA, Tejaswini et al [10] they rented a Merkle hash tree. Rivest, a Shamir Adleman (RSA)-based cryptographic system, maintains data confidentiality, while Jadhav et al [11] created an offensive module that constantly monitors data changes in the cloud.…”

Section: Introductionmentioning

confidence: 99%

A New Framework Approach Enhances Security to Efficient Remote Collaboration in TPA Scheme for Cloud Storage

Reddy¹

2021

IJRASET

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Cloud computing provides customers with storage as a service, allowing data to be stored, managed, and cached remotely. Users can also access it online. A major concern for users is the integrity of the data stored in the cloud, as it is possible for external invaders or criminals to attack, repair, or destroy the data stored in the cloud. Data auditing is a trending concept that involves hiring a third-party auditor to perform a data integrity test (TPA). The main purpose of this project is to provide a safe and effective testing system that combines features such as data integrity, confidentiality, and privacy protection. The cloud server is only used to store encrypted data blocks in the proposed system. It is not subject to any additional computer verification. TPA and the data owner are in charge of all the functions of the scheme. A variety of materials are used to evaluate the proposed audit process. The proposed solution meets all the processes while minimizing the load on cloud servers. Data dynamics actions such as data review, deletion, and installation will be performed in the future. Keywords: Cloud storage; Third Party Auditor; Public Auditing; Privacy Preserving; Integrity;

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Section: Introductionmentioning

confidence: 99%

A New Framework Approach Enhances Security to Efficient Remote Collaboration in TPA Scheme for Cloud Storage

Reddy¹

2021

IJRASET

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“…Most existing solutions (e.g., [13][14][15][16]) employ encryption/ decryption techniques combined with access control and auditing system to provide security and privacy for data stored on a public cloud. Different approaches are used to outsource health care data.…”

Section: Introductionmentioning

confidence: 99%

A Combined Clustering and Geometric Data Perturbation Approach for Enriching Privacy Preservation of Healthcare Data in Hybrid Clouds

Vulapula¹,

Rao²

2018

IJIES

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Abstract:In this paper, we plan a combined clustering and geometric data perturbation approach for improving privacy preservation of health care data in hybrid clouds. We will possibly plan an answer that can productively give protection to information put away in the cloud without presenting substantial overhead on both computation and communication. At first, the high-dimensional data are separated into various parts by utilizing the K-mean clustering method, each partition is considered as a cluster. At that point the mean estimate of each cluster processed; after that the contrast between the each cluster member and the mean of the cluster value is computed. In the next stage, the clustered information is perturbed by utilizing the Geometric Data Perturbation (GDP) algorithm which makes the values difficult to be recognized. These perturbed values are stored in the public cloud and the key parameters for randomizing and clustering is stored in the private cloud. Our approach would contribute in reduction of too much storage on private cloud on the off chance that we basically store the entire sensitive information on private clouds. The experimental results show that, the GDP algorithm has better privacy preserving compared with the other existing methods.

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Secure Data Integrity in Cloud Storage with Multi-level Hash Indexing Technique

Kavyashree¹,

Poornima²

2019

Sustainable Communication Networks and Application

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Privacy Preserving and Public Auditing Service for Data Storage in Cloud Computing

Cited by 10 publications

References 0 publications

A New Framework Approach Enhances Security to Efficient Remote Collaboration in TPA Scheme for Cloud Storage

A New Framework Approach Enhances Security to Efficient Remote Collaboration in TPA Scheme for Cloud Storage

A Combined Clustering and Geometric Data Perturbation Approach for Enriching Privacy Preservation of Healthcare Data in Hybrid Clouds

Secure Data Integrity in Cloud Storage with Multi-level Hash Indexing Technique

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