Abstract
Information sharing is the key goal of Storage servers. It allows storage of sensitive and large volume of data with limited cost and high access benefits. Security must be in given due importance for the cloud data with utmost care to the data and confidence to the data owner. But this limits the utilization of data through plain text search. Hence an excellent methodology is required to match the keywords with encrypted cloud data. The proposed approach similarity measure of “coordinate matching” combined with “inner product similarity” quantitatively evaluates and matches all relevant data with search keyword to arrive at best results. This approach, each document is associated with a binary vector to represent a keyword contained in the document. The search keyword is also described as a binary vector, so the similarity could be exactly measured by the inner product of the query vector with the data vector. The inner product computation and the two multi-keyword ranked search over encrypted data (MRSE) schemes ensures data privacy and provides detailed information about the dynamic operation on the data set and index and hence improves the search experience of the user.
Existing System
- The large number of data users and documents in cloud is crucial for the search service to allow multi-keyword query and provide result similarity ranking to meet the effective data retrieval need.
- The searchable encryption focuses on single keyword search or Boolean keyword search, and rarely differentiates the search results.
- By stop word concept the unwanted keywords will be removed.
- The document search by name not by content. so we get relevant information and irrelevant information.
- We are using MD5 algorithm in existing system.
Proposed System
- We define and solve the challenging problem of privacy-preserving multi-keyword ranked search over encrypted cloud data (MRSE), and establish a set of strict privacy requirements for such a secure cloud data utilization system to become a reality.
- Among various multi-keyword semantics, we choose the efficient principle of “coordinate matching”.
- In proposed system define public or private page and will be stored.
- Individual page updation is in this system.
- We ranking the document(abc.doc) by multi key word concept.
- Checksum value for each page.
Hardware Requirements
- System : Pentium IV and above.
- Hard Disk : 40 GB or Above
- Monitor : VGA and High-resolution Monitor
- Mouse : Logitech
- Ram : 1 GB or Above
Software Requirements
- Operating system : Windows VISTA or Above.
- Front End : Microsoft Visual Studio 2010 (.Net Framework 4.0)
- Coding Language : C# (CSHARP)
- Backend : Sql Server 2008 R2
Architecture Diagram
Project Modules
- Secure User Authentication
- Intelligent Name Search
- Stop Word Filtering
- Advanced Multi-Keyword Search
- Dynamic Page Updation
- Priority-Driven Search
- Performance Optimization & Evaluation
Components of Project Report
- Abstract
- Table of Contents
- List of Tables
- List of Figures
- Chapters
- Introduction
- Literature review
- Problem definition and requirement analysis
- Design and Implementation
- Testing and deployment
- Future enhancements
- Summary
- References
Project Report Pages : 80
Can be used in : Dotnet
Delivery Time : Within 2 hours.
Support / Query : Call +91-7449000533
Email [email protected]
