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A parallelized disjunctive query based searchable encryption scheme for big data
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DOI：10.1016/j.future.2018.05.048.png)
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Abstract
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Searchable Encryption (SE) allows a client to search over large amounts of encrypted data outsourced to the Cloud. Although, this helps to maintain the confidentiality of the outsourced data but achieving privacy is a difficult and resource intensive task. With the increase in the query effectiveness, i.e., by shifting from single keyword SE to multi-keyword SE there is a notable drop in the efficiency. This motivates to make use of the advances in the multi-core architectures and multiple threads where the search can be delegated across different threads to perform search in a parallel fashion. The proposed scheme is based on probabilistic trapdoors that are formed by making use of the property of modular inverses. The use of probabilistic trapdoors helps resist distinguishability attacks. The rigorous security analysis helps us to appreciate the advantage of having a probabilistic trapdoor. Furthermore, to validate the performance of the proposed scheme, it is implemented and deployed onto the British Telecommunication's Public Cloud offering and tested over a real speech corpus. The implementation is also extended to anticipate the performance gain by using the multi-core architecture that helps to maintain the lightweight property of the scheme. (C) 2018 Elsevier B.V. All rights reserved.
Keywords:
Searchable Encryption-as-a-Service (SEaaS)
Application encryption service
Probabilistic trapdoor
Privacy preservation
Inverted index
Multi-threading
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