Keyword Search Over Encrypted Data in Cloud Computing from Lattices in the Standard Model

2015 ◽  
pp. 335-343 ◽  
Author(s):  
Chunxiang Gu ◽  
Yonghui Zheng ◽  
Fei Kang ◽  
Dan Xin
Keyword(s):  
Cloud Computing ◽  
Standard Model ◽  
Keyword Search ◽  
Encrypted Data ◽  
The Standard Model

scholarly journals Efficient verifiable fuzzy keyword search over encrypted data in cloud computing

2013 ◽  
Vol 10 (2) ◽  
pp. 667-684 ◽  
Author(s):  
Jianfeng Wang ◽  
Hua Ma ◽  
Qiang Tang ◽  
Jin Li ◽  
Hui Zhu ◽  
...  
Keyword(s):  
Cloud Computing ◽  
Keyword Search ◽  
Efficiency Analysis ◽  
Sensitive Data ◽  
Encrypted Data ◽  
Proposed Model ◽  
Cloud Server ◽  
Encryption Schemes ◽  
User Data ◽  
Fuzzy Keyword Search

As cloud computing becomes prevalent, more and more sensitive data is being centralized into the cloud by users. To maintain the confidentiality of sensitive user data against untrusted servers, the data should be encrypted before they are uploaded. However, this raises a new challenge for performing search over the encrypted data efficiently. Although the existing searchable encryption schemes allow a user to search the encrypted data with confidentiality, these solutions cannot support the verifiability of searching result. We argue that a cloud server may be selfish in order to save its computation ability or bandwidth. For example, it may execute only a fraction of the search and returns part of the searching result. In this paper, we propose a new verifiable fuzzy keyword search scheme based on the symbol-tree which not only supports the fuzzy keyword search, but also enjoys the verifiability of the searching result. Through rigorous security and efficiency analysis, we show that our proposed scheme is secure under the proposed model, while correctly and efficiently realizing the verifiable fuzzy keyword search. The extensive experimental results demonstrate the efficiency of the proposed scheme.

scholarly journals Server-Aided Revocable Attribute-Based Encryption from Lattices

2020 ◽  
Vol 2020 ◽  
pp. 1-13
Author(s):  
Xingting Dong ◽  
Yanhua Zhang ◽  
Baocang Wang ◽  
Jiangshan Chen
Keyword(s):  
Access Control ◽  
Standard Model ◽  
Secret Key ◽  
Bilinear Maps ◽  
Encrypted Data ◽  
Fine Grained ◽  
Attribute Based Encryption ◽  
The Standard Model ◽  
Learning With Errors

Attribute-based encryption (ABE) can support a fine-grained access control to encrypted data. When the user’s secret-key is compromised, the ABE system has to revoke its decryption privileges to prevent the leakage of encrypted data. Although there are many constructions about revocable ABE from bilinear maps, the situation with lattice-based constructions is less satisfactory, and a few efforts were made to close this gap. In this work, we propose the first lattice-based server-aided revocable attribute-based encryption (SR-ABE) scheme and thus the first such construction that is believed to be quantum resistant. In the standard model, our scheme is proved to be secure based on the hardness of the Learning With Errors (LWE) problem.

scholarly journals Enabling Efficient Verifiable Fuzzy Keyword Search Over Encrypted Data in Cloud Computing

IEEE Access ◽  
2018 ◽  
Vol 6 ◽  
pp. 45725-45739 ◽  
Author(s):  
Xinrui Ge ◽  
Jia Yu ◽  
Chengyu Hu ◽  
Hanlin Zhang ◽  
Rong Hao
Keyword(s):  
Cloud Computing ◽  
Keyword Search ◽  
Encrypted Data ◽  
Fuzzy Keyword Search

Efficient fuzzy keyword search scheme over encrypted data in cloud computing based on Bed-tree index structure

2021 ◽  
pp. 1-13
Author(s):  
Dongping Hu ◽  
Aihua Yin
Keyword(s):  
Cloud Computing ◽  
Keyword Search ◽  
Hamming Distance ◽  
Security Analysis ◽  
Index Structure ◽  
Search Performance ◽  
Encrypted Data ◽  
Fuzzy Keyword Search ◽  
Work Security ◽  
And Performance

In cloud computing, enabling search directly over encrypted data is an important technique to effectively utilize encrypted data. Most of the existing techniques are focusing on fuzzy keyword search as it helps achieve more robust search performance by tolerating misspelling or typos of data users. Existing works always build index without classifying keywords in advance. They suffer from efficiency issue. Furthermore, Euclidean distance or Hamming distance is often chosen to evaluate strings’ similarity, ignoring prefixes matching and the influence of strings’ length on the accuracy. We propose an efficient fuzzy keyword search scheme with lower computation cost and higher accuracy to address the aforementioned problems. We employ the sub-dictionaries technique and the Bed-tree structure to build an index with three layers for achieving better search efficiency. With this index structure, the server could locate the keyword and could narrow the search scope quickly. The Jaro-Winkler distance is introduced to qualify the strings’ similarity by considering the prefixes matching and string length. The secure privacy mechanism is incorporated into the design of our work. Security analysis and performance evaluation demonstrate our scheme is more efficient compared to the existing one while guaranteeing security.

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