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

Efficient Fine Grained Access Control with Semantic Keyword Search on Encrypted Cloud Storage

Using cloud computing, multi data owner can store their data on remote servers and allow data access to private users through the cloud servers.The cloud characteristics are on-demand self-service, location independent network access, ubiquitous network access and usage based pay. Due to this charming features private and public organization are outsourcing their large amount of data on cloud storage. First, we introduce in the cloud framework for multi data owners. Multi data owners upload the files in encrypted form using ECC algorithm. User can register the aadhar card number to the cloud multi data owner. The multi data owner can generate the two keys to allow access the data. User can request to multi data owner. Cloud data storage can provide the encrypted data. This encrypted data is strong protection for data backup and recovery purposes. There are two keys are used in the plaintext form to be converted in the cipher text form. Another key will generate and converted in the decrypt form using fuzzy method and semantic search. Finally user can retrieve the data from the server and access our data.The existing solutions supports only identical keyword search, semantic search is not supported. In the project we proposed semantic multi-keyword ranked search system with verifiable outsourced decryption. To improve search efficiency this system includes semantic search by using fuzzy search

AI-enabled privacy-preservation phrase with multi-keyword ranked searching for sustainable edge-cloud networks in the era of industrial IoT

Abstract: Please refer to full text to view abstrac

A Novel Privacy Preserving Search Technique for Stego Data in Untrusted Cloud

We propose the first privacy preserving search technique for stego health data in untrusted cloud in this paper. The Cloud computing is a popular technology to the healthcare providers for outsourcing health data due to flexibility and cost effectiveness. However, outsourcing health data to the cloud introduces serious privacy issues to the patient. For example, dishonest personnel of the cloud provider may disclose patient sensitive information to business organizations for some financial benefits. Using steganography, patient sensitive information is hidden within health data for privacy preservation. As a result, stego health data is generated. To the best of our knowledge, no method exists for searching a particular stego data without disclosing any information to the cloud. We propose a framework for privacy preserving search over stego health data. We systematically describe each component of the proposed framework. We conduct several experiments to evaluate the performance of the framework

Privacy-preserving data outsourcing in the cloud via semantic data splitting

Even though cloud computing provides many intrinsic benefits, privacy concerns related to the lack of control over the storage and management of the outsourced data still prevent many customers from migrating to the cloud. Several privacy-protection mechanisms based on a prior encryption of the data to be outsourced have been proposed. Data encryption offers robust security, but at the cost of hampering the efficiency of the service and limiting the functionalities that can be applied over the (encrypted) data stored on cloud premises. Because both efficiency and functionality are crucial advantages of cloud computing, in this paper we aim at retaining them by proposing a privacy-protection mechanism that relies on splitting (clear) data, and on the distributed storage offered by the increasingly popular notion of multi-clouds. We propose a semantically-grounded data splitting mechanism that is able to automatically detect pieces of data that may cause privacy risks and split them on local premises, so that each chunk does not incur in those risks; then, chunks of clear data are independently stored into the separate locations of a multi-cloud, so that external entities cannot have access to the whole confidential data. Because partial data are stored in clear on cloud premises, outsourced functionalities are seamlessly and efficiently supported by just broadcasting queries to the different cloud locations. To enforce a robust privacy notion, our proposal relies on a privacy model that offers a priori privacy guarantees; to ensure its feasibility, we have designed heuristic algorithms that minimize the number of cloud storage locations we need; to show its potential and generality, we have applied it to the least structured and most challenging data type: plain textual documents

Authorized keyword search over outsourced encrypted data in cloud environment

For better data availability and accessibility while ensuring data secrecy, end-users often tend to outsource their data to the cloud servers in an encrypted form. However, this brings a major challenge to perform the search for some keywords over encrypted content without disclosing any information to unintended entities. This paper proposes a novel expressive authorized keyword search scheme relying on the concept of ciphertext-policy attribute-based encryption. The originality of the proposed scheme is multifold. First, it supports the generic and convenient multi-owner and multi-user scenario, where the encrypted data are outsourced by several data owners and searchable by multiple users. Second, the formal security analysis proves that the proposed scheme is semantically secure against chosen keyword and outsider's keyword guessing attacks. Third, an interactive protocol is introduced which avoids the need of any secure channels between users and service provider. Fourth, due to the concept of bilinear-map accumulator, the system can efficiently revoke users and/or their attributes, and authenticate them prior to launching any expensive search operations. Fifth, conjunctive keyword search is provided thus enabling to search for multiple keywords simultaneously, with minimal cost. Sixth, the performance analysis shows that the proposed scheme outperforms closely-related works