Paper 2019/1314 Original: eprint.iacr.org/2019/1314 ↗

Towards Privacy-Preserving and Efficient Attribute-Based Multi-Keyword Search

Zhidan Li
Wenmin Li
Fei Gao
Wei Yin
Hua Zhang
Qiaoyan Wen
Kaitai Liang
Abstract

Searchable encryption can provide secure search over encrypted cloud-based data without infringing data confidentiality and data searcher privacy. In this work, we focus on a secure search service providing fine-grained and expressive search functionality, which can be seen as a general extension of searchable encryption and called attribute-based multi-keyword search (ABMKS). In most of the existing ABMKS schemes, the ciphertext size of keyword index (encrypted index) grows linearly with the number of the keyword associated with a file, so that the computation and communication complexity of keyword index is limited to O(m) , where m is the number of the keyword. To address this shortage, we propose the first ABMKS scheme through utilizing keyword dictionary tree and the subset cover, in such a way that the ciphertext size of keyword index is not dependent on the number of underlying keyword in a file. In our design, the complexity of computation and the complexity of the keyword index are at most O ( 2· log (n/2) ) for the worst case, but O(1) for the best case, where n is the number of keyword in a keyword dictionary. We also present the security and the performance analysis to demonstrate that our scheme is both secure and efficient in practice.

Metadata
Available format(s)
PDF
Category
Cryptographic protocols
Publication info
Preprint.
History
2019-11-17: last updated
2019-11-17: published
Short URL
https://ia.cr/2019/1314
License
https://creativecommons.org/licenses/by/4.0/

BibTeX

@misc{cryptoeprint:2019/1314,
      author = {Zhidan Li and Wenmin Li and Fei Gao and Wei Yin and Hua Zhang and Qiaoyan Wen and Kaitai Liang},
      title = {Towards Privacy-Preserving and Efficient Attribute-Based Multi-Keyword Search},
      howpublished = {Cryptology {ePrint} Archive, Paper 2019/1314},
      year = {2019},
      url = {https://eprint.iacr.org/2019/1314}
}
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