758 research outputs found

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

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    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

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    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

    Towards a secure and efficient search over encrypted cloud data

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    Includes bibliographical references.2016 Summer.Cloud computing enables new types of services where the computational and network resources are available online through the Internet. One of the most popular services of cloud computing is data outsourcing. For reasons of cost and convenience, public as well as private organizations can now outsource their large amounts of data to the cloud and enjoy the benefits of remote storage and management. At the same time, confidentiality of remotely stored data on untrusted cloud server is a big concern. In order to reduce these concerns, sensitive data, such as, personal health records, emails, income tax and financial reports, are usually outsourced in encrypted form using well-known cryptographic techniques. Although encrypted data storage protects remote data from unauthorized access, it complicates some basic, yet essential data utilization services such as plaintext keyword search. A simple solution of downloading the data, decrypting and searching locally is clearly inefficient since storing data in the cloud is meaningless unless it can be easily searched and utilized. Thus, cloud services should enable efficient search on encrypted data to provide the benefits of a first-class cloud computing environment. This dissertation is concerned with developing novel searchable encryption techniques that allow the cloud server to perform multi-keyword ranked search as well as substring search incorporating position information. We present results that we have accomplished in this area, including a comprehensive evaluation of existing solutions and searchable encryption schemes for ranked search and substring position search

    Survey on Efficient Information Retrieval for Ranked Query in Cost-Efficient Clouds

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    Cloud computing technology redefines the advances in information technology. The most challenging research works in cloud computing is privacy and protection of data. Cloud computing provides an innovative business model for organizations with minimal investment. Cloud computing has emerged as a major driver in reducing the information technology costs incurred by organizations. Security is one of the major issues in cloud computing. So it is necessary to protect the user privacy while querying the data in the cloud environment, different techniques are developed by researchers to provide privacy, but the computational and bandwidth costs increased which are unacceptable to the users. This paper presents description and comparison of Ostrovsky, COPS and EIRQ protocols which are currently available for retrieving information from clouds. EIRQ protocol is the latest among these protocols and it addresses the issues of privacy, aggregation, CPU consumption and network bandwidth usage
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