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

EIRQ Methods to Provide a Cost-Efficient Solution for Private Searching in Cloud Computing

Abstract As a characteristic cloud application an organization pledge the cloud services and approves its team to share files in the cloud. Each file is explained by a set of keywords and the staff as authorized users can repossess files of their interests by querying the cloud with certain keywords. In such an environment how to protect user privacy from the cloud which is a third party outside the security boundary of the organization turn into a key problem. The communication cost acquires on the cloud will also be concentrated since files shared by the users need to be returned only once. Most significantly by using a series of secure functions COPS can protect user privacy from the ADL the cloud and other users. The main drawback is that it will cause a heavy querying overhead incurred on the cloud and thus goes against the original intention of cost efficiency. In this paper we present a method termed efficient information retrieval for ranked query (EIRQ) based on an aggregation and distribution layer (ADL) to condense querying overhead deserved on the cloud. Keywords Cloud Computing, Cost Efficiency, Differential Query Services, Privacy I. Introduction User privacy can be classified into search privacy and access privacy. Search privacy means that the cloud knows nothing about what the user is searching for and access privacy means that the cloud knows nothing about which files are returned to the user. When the files are stored in the clear forms a immature solution to protect user privacy is for the user to request all of the files from the cloud. This way the cloud cannot know which files the user is really interested in. While this does provide the necessary privacy and the communication cost is high. The ADL deployed inside an organization has two main functionalities, aggregating user queries and distributing search results. Under the ADL the computation cost incurred on the cloud can be basically condensed since the cloud only needs to complete a combined query once no matter how many users are executing queries. Under different parameter settings, extensive evaluations have been conducted on both analytical models and on a real cloud environment, in order to examine the effectiveness of our schemes. In EIRQ queries are classified into multiple ranks where a higher ranked query can regain a senior percentage of matched files. A user can retrieve files on demand by choosing queries of different ranks

An Analysis on Differential Query Services in Cost–Efficient Clouds

— In the simplest terms, cloud computing means storing and accessing data and programs over the Internet instead of your computer's hard drive. The cloud is just a metaphor for the Internet. Now a days Cloud computing as an emerging technology trend is expected to reshape the advances in information technology. In a cost-efficient cloud environment, a user can tolerate a certain degree of delay while retrieving information from the cloud to reduce costs. In this paper, i am address two fundamental issues in such an environment: privacy and efficiency. My first review a private keyword-based file retrieval scheme that was originally proposed by Ostrovsky. Their scheme allows a user to retrieve files of interest from an untrusted server without leaking any information. The main drawback is that it will cause a heavy querying overhead incurred on the cloud and thus goes against the original intention of cost efficiency. In this paper, present three efficient information retrieval for ranked query (EIRQ) schemes to reduce querying overhead incurred on the cloud. In EIRQ, queries are classified into multiple ranks, where a higher ranked query can retrieve a higher percentage of matched files. A user can retrieve files on demand by choosing queries of different ranks. This feature is useful when there are a large number of matched files, but the user only needs a small subset of them. Under different parameter settings, extensive evaluations have been conducted on both analytical models and on a real cloud environment, in order to examine the effectiveness of our schemes

Indexing encrypted documents for supporting efficient keyword search

10.1007/978-3-642-32873-2_7Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)7482 LNCS93-11