scholarly journals A Survey on Secure Ranked Keyword Search over Outsourced Encrypted Cloud Data

2021 ◽  
Vol 9 (VI) ◽  
pp. 949-952
Author(s):  
Akash Tidke
Keyword(s):  
Comparative Study ◽  
Keyword Search ◽  
Encrypted Data ◽  
Cloud Data ◽  
Ranked Search ◽  
Ranked Keyword Search ◽  
Cloud Servers

In this paper we present a survey on keyword based searching algorithms. Various searching techniques are used for retrieving the encrypted data from cloud servers. This survey work involves a comparative study of these keyword based searching algorithms. It concludes that till now multi-keyword ranked search MRSE scheme is the best methodology for searching the encrypted data.

PIMRS: achieving privacy and integrity-preserving multi-owner ranked-keyword search over encrypted cloud data

2016 ◽  
Vol 9 (16) ◽  
pp. 3765-3776 ◽  
Author(s):  
Jinguo Li ◽  
Mi Wen ◽  
Kejie Lu ◽  
Chunhua Gu
Keyword(s):  
Keyword Search ◽  
Cloud Data ◽  
Ranked Keyword Search

Enabling Secure and Efficient Ranked Keyword Search over Outsourced Cloud Data

2012 ◽  
Vol 23 (8) ◽  
pp. 1467-1479 ◽  
Author(s):  
Cong Wang ◽  
Ning Cao ◽  
Kui Ren ◽  
Wenjing Lou
Keyword(s):  
Keyword Search ◽  
Cloud Data ◽  
Ranked Keyword Search

scholarly journals Secure Multi-keyword Similarity Search Over Encrypted Data With Security Improvement

2021 ◽  
Vol 17 (2) ◽  
pp. 1-10
Author(s):  
Hussein Mohammed ◽  
Ayad Abdulsada
Keyword(s):  
Real World ◽  
Similarity Search ◽  
Keyword Search ◽  
Bloom Filter ◽  
Locality Sensitive Hashing ◽  
Real World Data ◽  
Encrypted Data ◽  
Search Results ◽  
Security Properties ◽  
Cloud Servers

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.

scholarly journals Secure and Dynamic Multi-Keyword Ranked Search Scheme Over Encrypted Cloud Data Using K-Means Clustering

2019 ◽  
pp. 230-235
Author(s):  
Tarika P. Jawale ◽  
R. B. Mapari
Keyword(s):  
Cloud Computing ◽  
Information Needs ◽  
Document Retrieval ◽  
Index Structure ◽  
Sensitive Information ◽  
Cloud Data ◽  
Index Vector ◽  
Ranked Search ◽  
Information Dynamic ◽  
Cloud Servers

A Secure and Dynamic Multi-keyword graded Search theme over Encrypted Cloud information attributable to the increasing fame of cloud computing, a lot of information homeowners are spurred to source their information to cloud servers for unimaginable accommodation and diminished expense in information management can also perform information dynamic operations on files. On the opposite hand, sensitive information needs to be encrypted before outsourcing for security conditions, that obsoletes information use like keyword-based document retrieval. A protected multi-keyword graded search theme over encrypted cloud information, that all the whereas underpins part update operations like deletion and insertion of documents. Especially, the vector area model and therefore the usually utilised TF_IDF model are consolidated as a neighbourhood of the index development and question generation. A unique tree-based index structure employing a "K-means Clustering" formula to provide practiced multi-keyword graded search. The secure KNN formula is employed to cipher the index and question vectors, so guarantee precise importance score calculation between encrypted index and question vectors. With a selected finish goal to oppose measurable attacks, phantom terms are accessorial to the index vector for glaring search results. Due to the employment of our exceptional tree-based index structure. Keyword: Reduplication, Authorized duplicate check, public auditing, shared data, Cloud computing.

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