Abstract
Searchable encryption has become a very important technique for secure data search in cloud systems. It can conduct search functions over encrypted cloud data and protect the data privacy meanwhile. There are many searchable encryption schemes that support basic search functions like single keyword search, multi-keyword search, similiarity search and so on. To enrich the search functionality, several searchable encryption schemes that support semantic search have been proposed recently. However, these schemes only focus on the existence of keywords during the search process. They have not considered the semantic relation between keywords, which have significant influence on the search results.
To solve this problem, in this paper, we propose a new co-occurrence matrix based Semantic Multi-keyword Ranked Search scheme (SMRS) which considers both the semantic relation of keywords and keyword weight for more accurate search results over encrypted cloud data. We design a term co-occurrence matrix to quantize the semantic correlation of keywords and adopt the widely-used TF-IDF rule to measure the keyword weight. In particular, our scheme can effectively retrieve data items that match the users’ intention better. The indexes and queries are encrypted by the secure kNN algorithm. We also add some randomness in the encryption process for stronger protection. Security analysis prove that SMRS is secure under the known background model. The performance evaluation shows that our scheme achieves high search accuracy and practical search efficiency.
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Acknowledgment
This work is supported by the National Natural Science Foundation of China (No. 61672195, 61379144, 61572026), Foundation of Science and Technology on Information Assurance Laboratory (No. KJ-15-001).
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Jia, N., Fu, S., Wang, D., Xu, M. (2018). A Co-occurrence Matrix Based Multi-keyword Ranked Search Scheme over Encrypted Cloud Data. In: Sun, X., Pan, Z., Bertino, E. (eds) Cloud Computing and Security. ICCCS 2018. Lecture Notes in Computer Science(), vol 11063. Springer, Cham. https://doi.org/10.1007/978-3-030-00006-6_4
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DOI: https://doi.org/10.1007/978-3-030-00006-6_4
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