학술논문

Fast Privacy-Preserving Keyword Search on Encrypted Outsourced Data
Document Type
Conference
Source
2019 IEEE International Conference on Big Data (Big Data) Big Data (Big Data), 2019 IEEE International Conference on. :1-10 Dec, 2019
Subject
Bioengineering
Communication, Networking and Broadcast Technologies
Computing and Processing
General Topics for Engineers
Geoscience
Signal Processing and Analysis
Transportation
Cryptography
Encryption
Big Data
Cloud computing
Servers
Keyword search
Data models
big data
data privacy
security
encryption
privacy-preserving
keyword search
information retrieval
Language
Abstract
Cloud providers offer storage as a service to the data owners to store emails and files on the cloud server. However, sensitive data should be encrypted before storing on the cloud server to avoid privacy concerns. With the encryption of documents, it is not feasible for data owners to retrieve documents based on keyword search as they can do with plain text documents. Hence, it is desirable to perform a multi-keyword search on encrypted data. To achieve this goal, we present a fast privacy-preserving model for keyword search on encrypted outsourced data in this paper. Specifically, the model first performs a keyword search on encrypted data and checks its support for dynamic operations. Based on keyword search results, it then sorts all the relevant data documents using the number of keywords matched for a given query. To evaluate its performance of our model, we applied the standard metrics like precision and recall. The results show the effectiveness of our privacy-preserving keyword search on encrypted outsourced data.