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dc.contributor.authorSalam, M.
dc.contributor.authorYau, W.
dc.contributor.authorChin, J.
dc.contributor.authorHeng, S.
dc.contributor.authorLing, Huo Chong
dc.contributor.authorPhan, R.
dc.contributor.authorPoh, G.
dc.contributor.authorTan, S.
dc.contributor.authorYap, W.
dc.identifier.citationSalam, M. and Yau, W. and Chin, J. and Heng, S. and Ling, H.C. and Phan, R. and Poh, G. et al. 2015. Implementation of searchable symmetric encryption for privacy-preserving keyword search on cloud storage. Human-centric Computing and Information Sciences. 5 (19).

Ensuring the cloud data security is a major concern for corporate cloud subscribers and in some cases for the private cloud users. Confidentiality of the stored data can be managed by encrypting the data at the client side before outsourcing it to the remote cloud storage server. However, once the data is encrypted, it will limit server’s capability for keyword search since the data is encrypted and server simply cannot make a plaintext keyword search on encrypted data. But again we need the keyword search functionality for efficient retrieval of data. To maintain user’s data confidentiality, the keyword search functionality should be able to perform over encrypted cloud data and additionally it should not leak any information about the searched keyword or the retrieved document. This is known as privacy preserving keyword search. This paper aims to study privacy preserving keyword search over encrypted cloud data. Also, we present our implementation of a privacy preserving data storage and retrieval system in cloud computing. For our implementation, we have chosen one of the symmetric key primitives due to its efficiency in mobile environments. The implemented scheme enables a user to store data securely in the cloud by encrypting it before outsourcing and also provides user capability to search over the encrypted data without revealing any information about the data or the query.

dc.publisherspringer berlin
dc.titleImplementation of searchable symmetric encryption for privacy-preserving keyword search on cloud storage
dc.typeJournal Article
dcterms.source.titleHuman-centric Computing and Information Sciences
curtin.departmentCurtin Sarawak
curtin.accessStatusOpen access via publisher

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