Dynamic Keyword Search With Hierarchical Attributes in Cloud Computing
Author(s) -
Tao Peng,
Qin Liu,
Baishuang Hu,
Jierong Liu,
Jiawei Zhu
Publication year - 2018
Publication title -
ieee access
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.587
H-Index - 127
ISSN - 2169-3536
DOI - 10.1109/access.2018.2878268
Subject(s) - aerospace , bioengineering , communication, networking and broadcast technologies , components, circuits, devices and systems , computing and processing , engineered materials, dielectrics and plasmas , engineering profession , fields, waves and electromagnetics , general topics for engineers , geoscience , nuclear engineering , photonics and electrooptics , power, energy and industry applications , robotics and control systems , signal processing and analysis , transportation
A growing number of organizations and individuals outsource their data to the cloud. As the cloud service provider is potentially untrustworthy, cloud user needs to encrypt their sensitive data before outsourcing. One challenge of the cloud service is how to provide an effective search on encrypted data while preserving user privacy. The existing attribute-based keyword search (ABKS) scheme has addressed this issue and enabled a data owner to conduct the search over the outsourced data utilizing an access policy. However, the encryption cost in ABKS linearly increases with the number of attributes in the access policy. In this paper, we proposed a dynamic hierarchical ABKS (DHABKS) scheme to efficiently achieve fine-grained search authorization. We introduced the attribute hierarchy into access policy to improve the encryption performance of the scheme and devised a dynamic updating access policy to largely reduce the workload of the data owner. The efficiency and effectiveness of the DHABKS scheme are validated by extensive experiments using real data sets.
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