? Private Keyword-Search for Database Systems Against Insider Attacks
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Journal of Computer Science and Technology 2017, Vol. 32 Issue (3) :599-617    DOI: 10.1007/s11390-017-1745-8
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Private Keyword-Search for Database Systems Against Insider Attacks
Peng Jiang1,2, Yi Mu2, Senior Member, IEEE, Fuchun Guo2, Qiao-Yan Wen1
1. State Key Laboratory of Networking and Switching Technology, Beijing University of Posts and Telecommunications Beijing 100876, China;
2. Centre for Computer and Information Security Research, School of Computing and Information Technology University of Wollongong, Wollongong, NSW 2522, Australia

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Abstract The notion of searchable encrypted keywords introduced an elegant approach to retrieve encrypted data without the need of decryption. Since the introduction of this notion, there are two main searchable encrypted keywords techniques, symmetric searchable encryption (SSE) and public key encryption with keyword search (PEKS). Due to the complicated key management problem in SSE, a number of concrete PEKS constructions have been proposed to overcome it. However, the security of these PEKS schemes was only weakly defined in presence of outsider attacks; therefore they suffer from keyword guessing attacks from the database server as an insider. How to resist insider attacks remains a challenging problem. We propose the first searchable encrypted keywords against insider attacks (SEK-IA) framework to address this problem. The security model of SEK-IA under public key environment is rebuilt. We give a concrete SEK-IA construction featured with a constant-size trapdoor and the proposed scheme is formally proved to be secure against insider attacks. The performance evaluations show that the communication cost between the receiver and the server in our SEK-IA scheme remains constant, independent of the sender identity set size, and the receiver needs the minimized computational cost to generate a trapdoor to search the data from multiple senders.
Articles by authors
Peng Jiang
Yi Mu
Fuchun Guo
Qiao-Yan Wen
Keywordspublic key encryption with keyword search   keyword privacy   insider attack   searchable encrypted keyword     
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This work is supported by the National Natural Science Foundation of China under Grant Nos. 61300181 and 61502044, and the Fundamental Research Funds for the Central Universities of China under Grant No. 2015RC23.

Corresponding Authors: 10.1007/s11390-017-1745-8   
About author: Peng Jiang received her B.S. degree in mathematics from Southeast University, Nanjing, in 2010. She is currently a Ph.D. candidate in the Department of State Key Laboratory of Networking and Switch Technology, Beijing University of Posts and Telecommunications, Beijing. She is also a visiting Ph.D. student at the School of Computing and Information Technology, University of Wollongong, Wollongong. Her research interests include information security and privacy concerns.
Cite this article:   
Peng Jiang, Yi Mu, Fuchun Guo, Qiao-Yan Wen.Private Keyword-Search for Database Systems Against Insider Attacks[J]  Journal of Computer Science and Technology, 2017,V32(3): 599-617
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http://jcst.ict.ac.cn:8080/jcst/EN/10.1007/s11390-017-1745-8
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