Toward a big data approach for indexing encrypted data in Cloud Computing

Abstract : Searchable encryption provides encryption schemes allowing search on encrypted data without decrypting the whole collection. However, due to the huge amount of data that exists in the Cloud, it is required to review such encryption schemes to decrease search and indexation times. In this paper, we propose a big data approach called MR-Index (MapReduce Indexation) that makes the indexation mechanism parallel. In fact, the proposed MR-Index is composed of two phases: Map phase and Reduce phase. In the Map phase, MR-Index processes documents in parallel to build for each keyword, the list of identifiers of documents containing it. Access control is ensured through Attribute Based Encryption (ABE). In the reduce phase of MR-Index, the data structures of the index are constructed. The MR-Index is performed by a trusted party called Searchable Encryption Authority (SEA). Experimental results, shown that the proposed solution decreases the indexation time for large documents, compared to the original sequential indexation mechanism. In terms of scalability of the solution, we ameliorated the MR-Index using the Hadoop archive files.
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Contributor : Abderrezak Rachedi <>
Submitted on : Tuesday, February 5, 2019 - 10:45:12 PM
Last modification on : Wednesday, March 20, 2019 - 12:04:53 AM

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Abdellah Kaci, Thouraya Bouabana-Tebibel, Abderrezak Rachedi, Chafia Yahiaoui. Toward a big data approach for indexing encrypted data in Cloud Computing. Security and Privacy journal, Wiley, 2019, ⟨10.1002/spy2.65⟩. ⟨hal-02008841⟩



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