Download Fast Range Query Processing with Strong Privacy Protection for

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.