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Cryptanalysis of a Privacy Preserving Ranked Multi-keyword Search Scheme in Cloud Computing

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Book cover Advanced Information Networking and Applications (AINA 2021)

Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 227))

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Abstract

Nowadays outsourcing data to cloud servers is a popular data management way for many users. But how to ensure the security and the usability of the outsourced data is a very challenge problem. Usually encryption of the outsourced data is a good way to protect the privacy. But after encryption, the usability always loses, such as how to search over the outsourced data. Aiming at solving this problem, recently Zhang et al. proposed a privacy preserving ranked multi-keyword search scheme for multiple data owners in cloud computing [IEEE Transactions on Computers, 65(5), 1566–1577, 2018]. However, in this short paper we find their scheme is not secure. Concrete, the adversary can forge the search trapdoor for any keyword, which invalidates the security goal of their original design.

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Acknowledgements

This work is supported by National Key Research and Development Program of China Under Grants No. 2017YFB0802000, National Nature Science Foundation of China (Grant Nos. 61572521, U1636114), National Cryptography Development Fund of China Under Grants No. MMJJ20170112, Natural Science Basic Research Plan in Shaanxi Province of china (Grant Nos. 2018JM6028), and an Open Project from Guizhou Provincial Key Laboratory of Public Big Data under Grant No. 2019BDKFJJ008. This work is also supported by Engineering University of PAP’s Funding for Scientific Research Innovation Team (No. KYTD201805), Engineering University of PAP’s Funding for Key Researcher (No. KYGG202011).

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Wang, X.A. (2021). Cryptanalysis of a Privacy Preserving Ranked Multi-keyword Search Scheme in Cloud Computing. In: Barolli, L., Woungang, I., Enokido, T. (eds) Advanced Information Networking and Applications. AINA 2021. Lecture Notes in Networks and Systems, vol 227. Springer, Cham. https://doi.org/10.1007/978-3-030-75078-7_37

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