Journal
IEEE TRANSACTIONS ON INFORMATION FORENSICS AND SECURITY
Volume 12, Issue 8, Pages 1874-1884Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TIFS.2017.2692728
Keywords
Searchable encryption; cloud computing; smart semantic search; conceptual graphs
Funding
- National Science Foundation of China [61232016, 61373133, U1536206, U1405254]
- PAPD Fund
- Jiangsu Collaborative Innovation Center on Atmospheric Environment and Equipment Technology
- Qing Lan Project
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Searchable encryption is an important research area in cloud computing. However, most existing efficient and reliable ciphertext search schemes are based on keywords or shallow semantic parsing, which are not smart enough to meet with users' search intention. Therefore, in this paper, we propose a content-aware search scheme, which can make semantic search more smart. First, we introduce conceptual graphs (CGs) as a knowledge representation tool. Then, we present our two schemes (PRSCG and PRSCG-TF) based on CGs according to different scenarios. In order to conduct numerical calculation, we transfer original CGs into their linear form with some modification and map them to numerical vectors. Second, we employ the technology of multi-keyword ranked search over encrypted cloud data as the basis against two threat models and raise PRSCG and PRSCG-TF to resolve the problem of privacy-preserving smart semantic search based on CGs. Finally, we choose a real-world data set: CNN data set to test our scheme. We also analyze the privacy and efficiency of proposed schemes in detail. The experiment results show that our proposed schemes are efficient.
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