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Fast Range Query Processing with Strong Privacy Protection for Cloud Computing Abstract ========= Privacy has been the key road block to cloud computing as clouds may not be fully trusted. This paper concerns the problem of privacy preserving range query processing on clouds. Prior schemes are weak in privacy protection as they cannot achieve index indistinguishability, and therefore allow the cloud to statistically estimate the values of data and queries using domain knowledge and history query results. In this paper, we propose the first range query processing scheme that achieves index indistinguishability under the indistinguishability against chosen keyword attack (INDCKA). Our key idea is to organize indexing elements in a complete binary tree called PBtree, which satisfies structure indistinguishability (i.e., two sets of data items have the same PBtree structure if and only if the two sets have the same number of data items) and node indistinguishability (i.e., the values of PBtree nodes are completely random and have no statistical meaning). We prove that our scheme is secure under the widely adopted IND-CKA security model. We propose two algorithms, namely PBtree traversal width minimization and PBtree traversal depth minimization, to improve query processing efficiency. We prove that the worse case complexity of our query processing algorithm using PBtree, where n is the total number of data items and R is the set of data items in the query result. We implemented and evaluated our scheme on a real world data set with 5 million items. Front End (MVC RAZOR) Back End (SQL Server) Software Tools (Visual Studio 2012, SQL 2008). Doctor: 1. Doctor login to the System. 2. Doctor Search to the Patient detail. 3. Doctor view patient sensitive data. Admin: 1. Admin upload the patient details. 2. Admin view the patient details. 3. Admin view the Patient Sensitive details using PB Tree. 4. Admin Analysis the patient details using JQuery datatable. Cloud: 1. Cloud Accept the Doctor Register Detail. 2. Cloud Analysis the Patient Details. 3. Cloud Provide the report for the patient details through chart view 1. Database -> Online Social (As My Database) ->I am using entity framework Controller 1. Admin controller 2. Home controller 3. Doctor controller Angular Controller 1.Part6 Controller 2. Part7 Controller There are 3 Mvc Controller and 2 Angular Controller have been created based on the Action method. SYSTEM ANALYSIS EXISTING SYSTEM We cannot use existing database indexing structures like B+ trees because of two reasons. First, searching on such trees (such as B+ trees) requires the operation of testing which of two numbers is bigger; however, PBtrees cannot support such operations for the cloud because otherwise PBtrees will share the same weaknesses with prior order preserving schemes. Second, their structures for different sets of data items are often different even if the two sets have equal sizes; however, for any two sets of the same size, their PBtrees are required to have the same structure. PROPOSED SYSTEM In this paper, we propose the first privacy preserving range query scheme that achieves index indistinguishability. Our key idea for achieving index indistinguishability is to organize all indexing elements in a complete binary tree where each node is represented using a Bloom filter, which we call a PBtree (where “P” stands for privacy and “B” stands for Bloom filter). PBtrees allow us to achieve index indistinguishability because it has two important properties. First, a PBtree has the property of structure indistinguishability, that is, two sets of data items have the same PBtree structure if and only if the two sets have the same number of data items. The structure of the PBtree of a set of data items is determined solely by the set cardinality, not the value of data items. Second, a PBtree has the property of node in- distinguishability, that is, for any two PBtrees constructed from data sets of the same cardinality, which have the same structure, and for any two corresponding nodes of the two PBtrees, the values of the two nodes are not distinguishable. Thus, our scheme prevents cloud from performing statistical analysis on the index even with domain knowledge. ALGORITHM Query Processing Algorithm: Transform a high level query on a distributed database (i.e...Set of global relation) into an equivalent and efficient low level query (of relational algebra) on relation fragments. The process choosing a suitable execution strategy for processing query. PB Tree Construction Algorithm: PB-tree is a self-balancing tree data structure that keeps data sorted and allows searches, sequential access, insertions, and deletions in logarithmic time. The B-tree is a generalization of a binary search tree in that a node can have more than two children. Search Algorithm: A search algorithm is the step-by-step procedure used to locate specific data among a collection of data. It is considered a fundamental procedure in computing. In computer science, when searching for data, the difference between a fast application and a slower one often lies in the use of the proper search algorithm. Encryption Algorithm: A mathematical procedure for performing encryption on data. Through the use of an algorithm, information is made into meaningless cipher text and requires the use of a key to transform the data back into its original form. SYSTEM SPECIFICATION HARDWARE REQUIREMENTS: System : Pentium IV 2.4 GHz. Hard Disk : 40 GB. Floppy Drive : 1.44 Mb. Monitor : 14’ Colour Monitor. Mouse : Optical Mouse. Ram : 512 Mb. SOFTWARE REQUIREMENTS: Operating system : Windows 7 Ultimate. Coding Language : MVC 4 Razor Front-End : Visual Studio 2012 Professional. Data Base : SQL Server 2008. CONCLUSION In this paper, we propose the first range query processing scheme that achieves index indistinguishability, under the IND-CKA, which provides strong privacy guarantees. The key novelty of this paper is in proposing the PBtree data structure and associate algorithms for PBtree construction, searching, and optimization. We implemented and evaluated our scheme on a real world data set. The experimental results show that our scheme can efficiently support real time range queries with strong privacy protection.