A Privacy Preserving Repository for Data Integration across Data Sharing Services

Yau, Sik-Sang; Yin, Yin

doi:10.1109/tsc.2008.14

Cited by 28 publications

(28 citation statements)

References 20 publications

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“…Their study lack the discussion on different storage technologies and their impact on performance. Yau et al [20] state that data integrity is among the main concerns cloud providers have. Their study focus on data integrity in clouds.…”

Section: Related Workmentioning

confidence: 99%

Towards Media Inter-cloud Standardization – Evaluating Impact of Cloud Storage Heterogeneity

2016

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Digital media has been increasing very rapidly, resulting in cloud computing's popularity gain. Cloud computing provides ease of management of large amount of data and resources. With a lot of devices communicating over the Internet and with the rapidly increasing user demands, solitary clouds have to communicate to other clouds to fulfill the demands and discover services elsewhere. This scenario is called inter-cloud computing or cloud federation. Inter-cloud computing still lacks standard architecture. Prior works discuss some of the architectural blue-prints, but none of them highlight the key issues involved and their impact, so that a valid and reliable architecture could be envisioned. In this paper, we discuss the importance of inter-cloud computing and present in detail its architectural components. Inter-cloud computing also involves some issues. We discuss key issues as well and present impact of storage heterogeneity. We have evaluated some of the most noteworthy cloud storage services, namely: Dropbox, Amazon CloudDrive, GoogleDrive, Microsoft OneDrive (formerly SkyDrive), Box, and SugarSync in terms of Quality of Experience (QoE), Quality of Service (QoS), and storage space efficiency. Discussion on the results shows the acceptability level of these storage services and the shortcomings in their design.

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Section: Related Workmentioning

confidence: 99%

Towards Media Inter-cloud Standardization – Evaluating Impact of Cloud Storage Heterogeneity

2016

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“…Yin and Yau [16] propose a privacy preserving repository for data integration across data sharing services that allows owners to specify integration requirements and data sharing services to safeguard their privacy. The owners determine who and how their data can be used.…”

Section: Related Workmentioning

confidence: 99%

Privacy Preserving Record Matching Using Automated Semi-trusted Broker

Lazrig

Moataz

Ray

et al. 2015

Lecture Notes in Computer Science

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Abstract. In this paper, we present a novel scheme that allows multiple data publishers that continuously generate new data and periodically update existing data, to share sensitive individual records with multiple data subscribers while protecting the privacy of their clients. An example of such sharing is that of health care providers sharing patients' records with clinical researchers. Traditionally, such sharing is performed by sanitizing personally identifying information from individual records. However, removing identifying information prevents any updates to the source information to be easily propagated to the sanitized records, or sanitized records belonging to the same client to be linked together. We solve this problem by utilizing the services of a third party, which is of very limited capabilities in terms of its abilities to keep a secret, secret, and by encrypting the identification part used to link individual records with different keys. The scheme is based on strong security primitives that do not require shared encryption keys.

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“…We assume that our data storage will correctly construct the query plans for user's requirements, decompose query plans, discover and fetch data from distributed data sharing services, amalgamate all data together, and, finally, return the final results to users. Further, we assume that our data storage is granted the access to the shared data by all data sharing services, and all shared data is well protected [17]. Our data storage consists of two components: the query plan wrapper and the query plan executor.…”

Section: II System Architecturementioning

confidence: 99%

“…2, data storage will collect only the data required for user's requests. To formulate the privacy preserving data integration across data sharing services in the cloud, it is needed to define the query plan [17]:…”

Section: Priv Acy Preserving Query Plan Withmentioning

confidence: 99%

Privacy preserving model in cloud environment

Saxena

Pushkar

2014

2014 Conference on IT in Business, Industry and Government (CSIBIG)

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There is consistent growth in the field of cloud com p uting. These services can be utilized on p a yp er-use basis. The problem of disclosure of privacy occurs when data is exchanged in the cloud. The idea is to build privacy preserving model of storage, where data sharing services can update and control the access and usage of their shared data. In cloud computing, privacy preserving is an important issue and it needs to be considered at every phase of design. The paper proposes a metadata based storage methodology along with an encryption technique to provide additional security.This would serve as a helping note in strengthening the privacy preserving approaches in cloud computing.

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A Privacy Preserving Repository for Data Integration across Data Sharing Services

Cited by 28 publications

References 20 publications

Towards Media Inter-cloud Standardization – Evaluating Impact of Cloud Storage Heterogeneity

Towards Media Inter-cloud Standardization – Evaluating Impact of Cloud Storage Heterogeneity

Privacy Preserving Record Matching Using Automated Semi-trusted Broker

Privacy preserving model in cloud environment

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