Secure and Efficient Utilization of Encrypted Cloud Data using Multi-Keyword Ranked Search

Cloud Computing is a technology that provides services to users such as software as a service, platform as a service and storage as a service. These services are provided based on Pay-per-Use basis so these services are cost effective and flexible. Due to this advantage of cloud computing, the individuals as well as the enterprises are getting motivated to shift their local sensitive and huge data management system to cloud storage. But the sensitive data has to be encrypted before outsourcing in order to provide security to the data. After the data has outsourced it has to be utilized efficiently without losing the originality as it was stored. In this paper we provide a mechanism called ”Multi-keyword Ranked Search over Encrypted cloud data” that gives better and efficient searched result over the encrypted data taking multiple keywords as query, which obsoletes the tradition searching scheme based on plain text search. And we use a “Coordinate Matching” technique to find as many matches as possible and use “inner product similarity” to retrieve relevance search results. So if user wants to retrieve the data stored on cloud, he can specify the multiple keywords and rank for relevance retrieval of results. Finally results the user with top ranked files. DOI: 10.17762/ijritcc2321-8169.160415

A practical and secure multi-keyword search method over encrypted cloud data

Cloud computing technologies become more and more popular every year, as many organizations tend to outsource their data utilizing robust and fast services of clouds while lowering the cost of hardware ownership. Although its benefits are welcomed, privacy is still a remaining concern that needs to be addressed. We propose an efficient privacy-preserving search method over encrypted cloud data that utilizes minhash functions. Most of the work in literature can only support a single feature search in queries which reduces the effectiveness. One of the main advantages of our proposed method is the capability of multi-keyword search in a single query. The proposed method is proved to satisfy adaptive semantic security definition. We also combine an effective ranking capability that is based on term frequency-inverse document frequency (tf-idf) values of keyword document pairs. Our analysis demonstrates that the proposed scheme is proved to be privacy-preserving, efficient and effective

Achieving Secure and Efficient Cloud Search Services: Cross-Lingual Multi-Keyword Rank Search over Encrypted Cloud Data

Multi-user multi-keyword ranked search scheme in arbitrary language is a novel multi-keyword rank searchable encryption (MRSE) framework based on Paillier Cryptosystem with Threshold Decryption (PCTD). Compared to previous MRSE schemes constructed based on the k-nearest neighbor searcha-ble encryption (KNN-SE) algorithm, it can mitigate some draw-backs and achieve better performance in terms of functionality and efficiency. Additionally, it does not require a predefined keyword set and support keywords in arbitrary languages. However, due to the pattern of exact matching of keywords in the new MRSE scheme, multilingual search is limited to each language and cannot be searched across languages. In this pa-per, we propose a cross-lingual multi-keyword rank search (CLRSE) scheme which eliminates the barrier of languages and achieves semantic extension with using the Open Multilingual Wordnet. Our CLRSE scheme also realizes intelligent and per-sonalized search through flexible keyword and language prefer-ence settings. We evaluate the performance of our scheme in terms of security, functionality, precision and efficiency, via extensive experiments