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

Outsourced Analysis of Encrypted Graphs in the Cloud with Privacy Protection

Huge diagrams have unique properties for organizations and research, such as client linkages in informal organizations and customer evaluation lattices in social channels. They necessitate a lot of financial assets to maintain because they are large and frequently continue to expand. Owners of large diagrams may need to use cloud resources due to the extensive arrangement of open cloud resources to increase capacity and computation flexibility. However, the cloud's accountability and protection of schematics have become a significant issue. In this study, we consider calculations for security savings for essential graph examination practices: schematic extraterrestrial examination for outsourcing graphs in the cloud server. We create the security-protecting variants of the two proposed Eigen decay computations. They are using two cryptographic algorithms: additional substance homomorphic encryption (ASHE) strategies and some degree homomorphic encryption (SDHE) methods. Inadequate networks also feature a distinctively confidential info adaptation convention to allow the trade-off between secrecy and data sparseness. Both dense and sparse structures are investigated. According to test results, calculations with sparse encoding can drastically reduce information. SDHE-based strategies have reduced computing time, while ASHE-based methods have reduced stockpiling expenses

Longitude : a privacy-preserving location sharing protocol for mobile applications

Location sharing services are becoming increasingly popular. Although many location sharing services allow users to set up privacy policies to control who can access their location, the use made by service providers remains a source of concern. Ideally, location sharing providers and middleware should not be able to access users’ location data without their consent. In this paper, we propose a new location sharing protocol called Longitude that eases privacy concerns by making it possible to share a user’s location data blindly and allowing the user to control who can access her location, when and to what degree of precision. The underlying cryptographic algorithms are designed for GPS-enabled mobile phones. We describe and evaluate our implementation for the Nexus One Android mobile phone

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