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

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

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

Report on the Information Retrieval Festival (IRFest2017)

The Information Retrieval Festival took place in April 2017 in Glasgow. The focus of the workshop was to bring together IR researchers from the various Scottish universities and beyond in order to facilitate more awareness, increased interaction and reflection on the status of the field and its future. The program included an industry session, research talks, demos and posters as well as two keynotes. The first keynote was delivered by Prof. Jaana Kekalenien, who provided a historical, critical reflection of realism in Interactive Information Retrieval Experimentation, while the second keynote was delivered by Prof. Maarten de Rijke, who argued for more Artificial Intelligence usage in IR solutions and deployments. The workshop was followed by a "Tour de Scotland" where delegates were taken from Glasgow to Aberdeen for the European Conference in Information Retrieval (ECIR 2017

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

Study on A Proposed Scheme for Generating Inverted Encryption Index Structure Based on Public Homomorphic Encryption

This research article focuses on the formidable challenge of efficiently searching through encrypted data in cloud environments, particularly as an extended number of users adopt encryption for their sensitive Information. The inverted index has proven to be a robust and effective searchable index structure in this context. However, striking a balance between preserving user privacy and enabling conjunctive multi-keyword searches remains a significant hurdle for existing solutions. In response to this challenge, the authors propose an innovative public-key-based encrypted file system. This system follows conjunctive multi-keyword searches but also eliminates the restrictive one-time-only searching limitation that has been a drawback in previous approaches. The proposed solution goes beyond conventional methods by safeguarding the search pattern, a critical aspect of user privacy. Their approach involves the integration of a probabilistic trapdoor- generating mechanism, adding an extra layer of security. To fortify their technique and adhere to more stringent security standards, the authors introduce an oblivious transmission control mechanism. This mechanism enhances the overall security posture of the system, ensuring robust protection against potential threats. The simulation results presented in the article demonstrate the practical proposed technique in real-world applications. Despite the additional security measures, the approach incurs reasonable overhead, making it a viable and efficient solution for cloud-based encrypted data searches

Towards Differential Query Services in Taken a toll Efficient Clouds

Cloud computing as a developing innovation pattern is relied upon to reshape the advances in data innovation. In a cost efficient cloud environment, a client can endure a sure level of postponement while recovering data from the cloud to lessen costs. In this paper, we address two key issues in such a domain: privacy and efficiency. We first audit a private magic word based record recovery plot that was initially proposed by Ostrovsky. Their plan permits a client to recover documents of enthusiasm from an un trusted server without releasing any data. The fundamental downside is that it will bring about a substantial questioning overhead brought about on the cloud, and along these lines conflicts with the first aim of expense effectiveness. In this paper, we display a plan, efficient information retrieval for ranked query (EIRQ), in view of a Aggregation and distribution layer (ADL), to lessen questioning overhead brought about on the cloud. In EIRQ, queries are arranged into different positions, where a higher positioned query can recover a higher rate of coordinated records. A client can recover documents on interest by picking quires of diverse positions. This element is valuable when there are an extensive number of coordinated documents, yet the client just needs a little subset of them. Under diverse parameter settings, broad assessments have been led on both scientific models and on a genuine cloud environment, keeping in mind the end goal to look at the viability of our plans