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Security and Communication Networks
Volume 2017, Article ID 6435138, 16 pages
https://doi.org/10.1155/2017/6435138
Research Article

Multiuser Searchable Encryption with Token Freshness Verification

1Sarvajanik College of Engineering and Technology, Surat, Gujarat, India
2Sardar Vallabhbhai National Institute of Technology, Surat, Gujarat, India

Correspondence should be addressed to Dhruti Sharma; moc.liamg@77iturhdamrahs

Received 2 May 2017; Revised 25 September 2017; Accepted 25 October 2017; Published 26 November 2017

Academic Editor: Sherali Zeadally

Copyright © 2017 Dhruti Sharma and Devesh C. Jinwala. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

A Multiuser Searchable Encryption (MUSE) can be defined with the notion of Functional Encryption (FE) where a user constructs a search token from a search key issued by an Enterprise Trusted Authority (ETA). In such scheme, a user possessing search key constructs search token at any time and consequently requests the server to search over encrypted data. Thus, an FE based MUSE scheme is not suitable for the applications where a log of search activities is maintained at the enterprise site to identify dishonest search query from any user. In addition, none of the existing searchable schemes provides security against token replay attack to avoid reuse of the same token. In this paper, therefore we propose an FE based scheme, Multiuser Searchable Encryption with Token Freshness Verification (MUSE-TFV). In MUSE-TFV, a user prepares one-time usable search token in cooperation with ETA and thus every search activity is logged at the enterprise site. Additionally, by verifying the freshness of a token, the server prevents reuse of the token. With formal security analysis, we prove the security of MUSE-TFV against chosen keyword attack and token replay attack. With theoretical and empirical analysis, we justify the effectiveness of MUSE-TFV in practical applications.