Multi-Keyword Search Methodology for Cloud Data

Adaptive Multi-keyword Ranked Search Over Encrypted Cloud Data

Multi-keyword Similarity Search over Encrypted Cloud Data

Searchable encryption allows one to upload encrypted documents on a remote honest-but-curious server and query that data at the server itself without requiring the documents to be decrypted prior to searching. In this work, we propose a novel secure and efficient multi-keyword similarity searchable encryption (MKSim) that returns the matching data items in a ranked ordered manner. Unlike all pr...

Effective Cloud Search Based on Multi Keyword Ranked Over Encrypted Cloud Data

In recent years, consumer-centric cloud computing paradigm has emerged as the development of smart electronic devices combined with the emerging cloud computing technologies. A variety of cloud services are delivered to the consumers with the premise that an effective and efficient cloud search service is achieved. For consumers, they want to find the most relevant products or data, which is hi...

Secure and Dynamic Multi-keyword Ranked Search Scheme and Fuzzy Search over Encrypted Cloud Data

With the increased rate of growth and adaptation of cloud computing, daily, more and more sensitive information is being centralized onto the cloud. For the protection of valuable proprietary information, the data must be encrypted before outsourcing. There is no tolerance for typos and format inconsistencies which are normal user behavior. This makes effective data storage and utilization a ve...

Secure Multi-keyword Similarity Search Over Encrypted Cloud Data Supporting Efficient Multi-user Setup

Searchable encryption allows one to store encrypted documents on a remote honest-butcurious server, and query that data at the server itself without requiring the documents to be decrypted prior to searching. This not only protects the data from the prying eyes of the server, but can also reduce the communication overhead between the server and the user and local processing at the latter. Previ...