Dynamic Similarity Search over Encrypted Data with Low Leakage

Author(s):  
Daniel Homann ◽  
Christian Göge ◽  
Lena Wiese
2018 ◽  
Vol 12 (4) ◽  
pp. 893-911
Author(s):  
Jinguo Li ◽  
Mi Wen ◽  
Kui Wu ◽  
Kejie Lu ◽  
Fengyong Li ◽  
...  

2021 ◽  
Vol 17 (2) ◽  
pp. 1-10
Author(s):  
Hussein Mohammed ◽  
Ayad Abdulsada

Searchable encryption (SE) is an interesting tool that enables clients to outsource their encrypted data into external cloud servers with unlimited storage and computing power and gives them the ability to search their data without decryption. The current solutions of SE support single-keyword search making them impractical in real-world scenarios. In this paper, we design and implement a multi-keyword similarity search scheme over encrypted data by using locality-sensitive hashing functions and Bloom filter. The proposed scheme can recover common spelling mistakes and enjoys enhanced security properties such as hiding the access and search patterns but with costly latency. To support similarity search, we utilize an efficient bi-gram-based method for keyword transformation. Such a method improves the search results accuracy. Our scheme employs two non-colluding servers to break the correlation between search queries and search results. Experiments using real-world data illustrate that our scheme is practically efficient, secure, and retains high accuracy.


Author(s):  
Yandong Zheng ◽  
Rongxing Lu ◽  
Yunguo Guan ◽  
Jun Shao ◽  
Hui Zhu

2019 ◽  
Vol 13 (1) ◽  
pp. 61-69 ◽  
Author(s):  
Cheng Guo ◽  
Pengxu Tian ◽  
Chin-Chen Chang

2018 ◽  
Vol 107 (3) ◽  
pp. 1337-1353
Author(s):  
Changhee Hahn ◽  
Hyung June Shin ◽  
Hyunsoo Kwon ◽  
Junbeom Hur

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