Secure and flexible keyword search over encrypted data with outsourced decryption in Internet of things

2018 ◽  
Vol 74 (7-8) ◽  
pp. 413-421 ◽  
Author(s):  
Yinghui Zhang ◽  
Axin Wu ◽  
Tiantian Zhang ◽  
Dong Zheng
Keyword(s):  
Internet Of Things ◽  
Keyword Search ◽  
Encrypted Data ◽  
Outsourced Decryption

Time-Controlled Hierarchical Multi-keyword Search over Encrypted Data in Cloud-Assisted IoT

2021 ◽  
pp. 1-1
Author(s):  
Tong Liu ◽  
Yinbin Miao ◽  
Kim-Kwang Raymond Choo ◽  
Hongwei Li ◽  
Ximeng Liu ◽  
...  
Keyword(s):  
Keyword Search ◽  
Encrypted Data

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 Novel Multi-Keyword Search on Encrypted Data in the Cloud

IEEE Access ◽  
2019 ◽  
Vol 7 ◽  
pp. 31984-31996 ◽  
Author(s):  
Yunyun Wu ◽  
Jingyu Hou ◽  
Jing Liu ◽  
Wanlei Zhou ◽  
Shaowen Yao
Keyword(s):  
Keyword Search ◽  
Encrypted Data

scholarly journals A Lightweight Fine-Grained Search Scheme over Encrypted Data in Cloud-Assisted Wireless Body Area Networks

2019 ◽  
Vol 2019 ◽  
pp. 1-12 ◽  
Author(s):  
Mingsheng Cao ◽  
Luhan Wang ◽  
Zhiguang Qin ◽  
Chunwei Lou
Keyword(s):  
Keyword Search ◽  
Body Area Networks ◽  
Wireless Body Area Networks ◽  
Security And Privacy ◽  
Body Area ◽  
Encrypted Data ◽  
Fine Grained ◽  
Resource Limited ◽  
Attribute Based Encryption ◽  
Ciphertext Policy

The wireless body area networks (WBANs) have emerged as a highly promising technology that allows patients’ demographics to be collected by tiny wearable and implantable sensors. These data can be used to analyze and diagnose to improve the healthcare quality of patients. However, security and privacy preserving of the collected data is a major challenge on resource-limited WBANs devices and the urgent need for fine-grained search and lightweight access. To resolve these issues, in this paper, we propose a lightweight fine-grained search over encrypted data in WBANs by employing ciphertext policy attribute based encryption and searchable encryption technologies, of which the proposed scheme can provide resource-constraint end users with fine-grained keyword search and lightweight access simultaneously. We also formally define its security and prove that it is secure against both chosen plaintext attack and chosen keyword attack. Finally, we make a performance evaluation to demonstrate that our scheme is much more efficient and practical than the other related schemes, which makes the scheme more suitable for the real-world applications.

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