Notice of Retraction Privacy Preserving Similarity Based Text Retrieval through Blind Storage

Abstract

Notice of Retraction

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After careful and considered review of the content of this paper by a duly constituted expert committee, this paper has been found to be in violation of IAES's Publication Principles.

We hereby retract the content of this paper. Reasonable effort should be made to remove all past references to this paper.

The presenting author of this paper has the option to appeal this decision by contacting ijeei.iaes@gmail.com.

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Cloud computing is improving rapidly due to their more advantage and more data owners give interest to outsource their data into cloud storage for centralize their data. As huge files stored in the cloud storage, there is need to implement the keyword based search process to data user. At the same time to protect the privacy of data, encryption techniques are used for sensitive data, that encryption is done before outsourcing data to cloud server. But it is critical to search results in encryption data. In this system we propose similarity text retrieval from the blind storage blocks with encryption format. This system provides more security because of blind storage system. In blind storage system data is stored randomly on cloud storage.  In Existing Data Owner cannot encrypt the document data as it was done only at server end. Everyone can access the data as there was no private key concept applied to maintained privacy of the data. But In our proposed system, Data Owner can encrypt the data himself using RSA algorithm.  RSA is a public key-cryptosystem and it is widely used for sensitive data storage over Internet. In our system we use Text mining process for identifying the index files of user documents. Before encryption we also use NLP (Nature Language Processing) technique to identify the keyword synonyms of data owner document. Here text mining process examines text word by word and collect literal meaning beyond the words group that composes the sentence. Those words are examined in API of word net so that only equivalent words can be identified for index file use. Our proposed system provides more secure and authorized way of recover the text in cloud storage with access control. Finally, our experimental result shows that our system is better than existing.