Efficient searchable symmetric encryption for storing multiple source data on cloud

© 2015 IEEE. Cloud computing has greatly facilitated large-scale data outsourcing due to its cost efficiency, scalability and many other advantages. Subsequent privacy risks force data owners to encrypt sensitive data, hence making the outsourced data no longer searchable. Searchable Symmetric Encryption (SSE) is an advanced cryptographic primitive addressing the above issue, which maintains efficient keyword search over encrypted data without disclosing much information to the storage provider. Existing SSE schemes implicitly assume that original user data is centralized, so that a searchable index can be built at once. Nevertheless, especially in cloud computing applications, user-side data centralization is not reasonable, e.g. an enterprise distributes its data in several data centers. In this paper, we propose the notion of Multi-Data-Source SSE (MDS-SSE), which allows each data source to build a local index individually and enables the storage provider to merge all local indexes into a global index afterwards. We propose a novel MDS-SSE scheme, in which an adversary only learns the number of data sources, the number of entire data files, the access pattern and the search pattern, but not any other distribution information such as how data files or search results are distributed over data sources. We offer rigorous security proof of our scheme, and report experimental results to demonstrate the efficiency of our scheme

State of The Art and Hot Aspects in Cloud Data Storage Security

Along with the evolution of cloud computing and cloud storage towards matu- rity, researchers have analyzed an increasing range of cloud computing security aspects, data security being an important topic in this area. In this paper, we examine the state of the art in cloud storage security through an overview of selected peer reviewed publications. We address the question of defining cloud storage security and its different aspects, as well as enumerate the main vec- tors of attack on cloud storage. The reviewed papers present techniques for key management and controlled disclosure of encrypted data in cloud storage, while novel ideas regarding secure operations on encrypted data and methods for pro- tection of data in fully virtualized environments provide a glimpse of the toolbox available for securing cloud storage. Finally, new challenges such as emergent government regulation call for solutions to problems that did not receive enough attention in earlier stages of cloud computing, such as for example geographical location of data. The methods presented in the papers selected for this review represent only a small fraction of the wide research effort within cloud storage security. Nevertheless, they serve as an indication of the diversity of problems that are being addressed

Achieving Fine-grained Multi-keyword Ranked Search over Encrypted Cloud Data

With the advancement of Cloud computing, people now store their data on remote Cloud servers for larger computation and storage resources. However, users’ data may contain sensitive information of users and should not be disclosed to the Cloud servers. If users encrypt their data and store the encrypted data in the servers, the search capability supported by the servers will be significantly reduced because the server has no access to the data content. In this paper, we propose a Fine-grained Multi-keyword Ranked Search (FMRS) scheme over encrypted Cloud data. Specifically, we leverage novel techniques to realize multikeyword ranked search, which supports both mixed “AND”, “OR” and “NO” operations of keywords and ranking according to the preference factor and relevance score. Through security analysis, we can prove that the data confidentiality, privacy protection of index and trapdoor, and the unlinkability of trapdoor can be achieved in our FMRS. Besides, Extensive experiments show that the FMRS possesses better performance than existing schemes in terms of functionality and efficiency

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

A systematic literature review of cloud computing in eHealth

Cloud computing in eHealth is an emerging area for only few years. There needs to identify the state of the art and pinpoint challenges and possible directions for researchers and applications developers. Based on this need, we have conducted a systematic review of cloud computing in eHealth. We searched ACM Digital Library, IEEE Xplore, Inspec, ISI Web of Science and Springer as well as relevant open-access journals for relevant articles. A total of 237 studies were first searched, of which 44 papers met the Include Criteria. The studies identified three types of studied areas about cloud computing in eHealth, namely (1) cloud-based eHealth framework design (n=13); (2) applications of cloud computing (n=17); and (3) security or privacy control mechanisms of healthcare data in the cloud (n=14). Most of the studies in the review were about designs and concept-proof. Only very few studies have evaluated their research in the real world, which may indicate that the application of cloud computing in eHealth is still very immature. However, our presented review could pinpoint that a hybrid cloud platform with mixed access control and security protection mechanisms will be a main research area for developing citizen centred home-based healthcare applications