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Attribute-Based Keyword Search from Lattices

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Information Security and Cryptology (Inscrypt 2019)

Part of the book series: Lecture Notes in Computer Science ((LNSC,volume 12020))

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Abstract

Attribute-based keyword search (ABKS) is a special case of public key encryption with keyword search (PEKS) which allows fine-grained control of the search ability and can be further categorized into key-policy ABKS (KP-ABKS) and ciphertext-policy ABKS (CP-ABKS). In a KP-ABKS (resp., CP-ABKS) scheme, a trapdoor that is associated with an access policy f (resp., an attributes string \(\mathbf {x}\)) can only be used to search over ciphertexts that is associated with an attributes string \(\mathbf {x}\) (resp., an access policy f) if \(f(\mathbf {x})=0\). As ABKS is very useful in the era of big data, many researchers have been devoted to design ABKS schemes with different features, but almost all the known schemes are based on the traditional number-theoretical assumptions such as Factoring or Discrete Logarithm, and thus are insecure against quantum adversaries.

In this paper, we propose a lattice-based KP-ABKS scheme supporting circuit policy of any predetermined polynomial depth. Our scheme is provably secure against chosen keyword attacks and keyword guessing attacks under the DLWE and ISIS assumptions in the random oracle model. By using a universal circuit, our scheme can also be converted into a CP-ABKS scheme.

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Acknowledgments

We thank the anonymous Inscrypt’2019 reviewers for their helpful comments. This work was supported by the National Natural Science Foundation of China (Grant Nos. 61902111, 61672030, 61602046, 61932019), the National Key Research and Development Program of China (Grant Nos. 2017YFB0802005, 2018YFB0804105), and the Young Elite Scientists Sponsorship Program by CAST (Grant No. 2016QNRC001).

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Authors and Affiliations

  1. State Key Laboratory of Information Security, Institute of Information Engineering, Chinese Academy of Sciences, Beijing, China

    Jie Li & Shuaigang Li

  2. School of Cyber Security, University of Chinese Academy of Sciences, Beijing, China

    Jie Li & Shuaigang Li

  3. State Key Laboratory of Cryptology, Beijing, China

    Jie Li, Mimi Ma, Jiang Zhang, Shuqin Fan & Shuaigang Li

  4. College of Information Science and Engineering, Henan University of Technology, Zhengzhou, China

    Mimi Ma

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  1. Jie Li
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  1. College of Computer Science and Technology, Nanjing University of Aeronautics and Astronautics, Nanjing, China

    Zhe Liu

  2. Computer Science Department, Columbia University, New York, NY, USA

    Moti Yung

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Li, J., Ma, M., Zhang, J., Fan, S., Li, S. (2020). Attribute-Based Keyword Search from Lattices. In: Liu, Z., Yung, M. (eds) Information Security and Cryptology. Inscrypt 2019. Lecture Notes in Computer Science(), vol 12020. Springer, Cham. https://doi.org/10.1007/978-3-030-42921-8_4

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  • DOI: https://doi.org/10.1007/978-3-030-42921-8_4

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