Encrypted Document File Retrieval Using User Encrypted Query

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Introduction

As various issues are rise on the server, for instance, data dealing with, security, support, etc.. In this work document recovery is done with various approaches. As the written work of various articles from research center, association, squeeze media, establishments are expanding step by step. In case of text mining information is not hidden in form of any unknown form where extraction of information is very hard. One more issue in txt mining is the comprehension of the learning if there should be an occurrence of various human wordings, as sentence is diverse in various cases. So issue of data getting is not all that managable to programmed preparing of content archive. In any case, with the utilization of content mining approach report is changing over into suitable configuration so PC can undoubtedly process entire archive. In this work a catchphrase based calculation is suggested that order the content report in productive way. Modulus indexing of the dataset document was done by utilizing term features. In order to provide privacy for the terms each of this is identified by a unique number and each document has its own index key for identification. After perfect classification of document retrieval of document as per text query is done. As AES encryption was utilized by the work so protection of the archive was kept up.

PROBLEM IN EXISTING METHOD-

• Here regular words are approved in tree data arrangement where levels increase as per number of keywords. 
• There is separate path For each term and document be that as it may, number of way increments as number of reports are expanding, so including of new archive is stopped complex.
• So to find the new record recursive steps are required for other related reports which is quit time consuming. 

PROPOSED SOLUTION

In this work document retrieval was proposed that efficiently the fetch document as per query.  Here hash based indexing of the dataset document was done by utilizing term features. In order to provide privacy for the terms each of this is identified by a unique number and each document has its hash index key for identification. Proposed work has increase the retrieval efficiency of the work in all different evaluation parameters. So use of hash based indexing provides privacy with efficiency for document retrieval.

Whole work is divided into two modules:

1. Training  module
2. Testing  module

In training module hash index was proposed while testing module user pass query.

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