Please use this identifier to cite or link to this item: https://doi.org/10.3390/a10020052
Title: Searchable data vault: Encrypted queries in secure distributed cloud storage
Authors: Poh, G.S 
Baskaran, V.M
Chin, J.-J 
Mohamad, M.S
Lee, K.W
Maniam, D
Z'aba, M.R
Keywords: Cryptography
Digital storage
Cloud securities
Cloud storage services
Computation overheads
Distributed clouds
Encrypted data
Privacy concerns
Storage servers
Symmetric encryption
Search engines
Issue Date: 2017
Publisher: MDPI AG
Citation: Poh, G.S, Baskaran, V.M, Chin, J.-J, Mohamad, M.S, Lee, K.W, Maniam, D, Z'aba, M.R (2017). Searchable data vault: Encrypted queries in secure distributed cloud storage. Algorithms 10 (2) : 52. ScholarBank@NUS Repository. https://doi.org/10.3390/a10020052
Rights: Attribution 4.0 International
Abstract: Cloud storage services allow users to ef?ciently outsource their documents anytime and anywhere. Such convenience, however, leads to privacy concerns. While storage providers may not read users' documents, attackers may possibly gain access by exploiting vulnerabilities in the storage system. Documents may also be leaked by curious administrators. A simple solution is for the user to encrypt all documents before submitting them. This method, however, makes it impossible to ef?ciently search for documents as they are all encrypted. To resolve this problem, we propose a multi-server searchable symmetric encryption (SSE) scheme and construct a system called the searchable data vault (SDV). A unique feature of the scheme is that it allows an encrypted document to be divided into blocks and distributed to different storage servers so that no single storage provider has a complete document. By incorporating the scheme, the SDV protects the privacy of documents while allowing for ef?cient private queries. It utilizes a web interface and a controller that manages user credentials, query indexes and submission of encrypted documents to cloud storage services. It is also the ?rst system that enables a user to simultaneously outsource and privately query documents from a few cloud storage services. Our preliminary performance evaluation shows that this feature introduces acceptable computation overheads when compared to submitting documents directly to a cloud storage service. © 2017 by the authors.
Source Title: Algorithms
URI: https://scholarbank.nus.edu.sg/handle/10635/179714
ISSN: 1999-4893
DOI: 10.3390/a10020052
Rights: Attribution 4.0 International
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