Cryptographic Data Retrieval from Cloud by Hashing and Indexing Technique

Authors(2) :-Arpita Porwal, Deepak Shukla

Since in this era, Cloud computing becoming more and more popular by accelerating huge quantity of data storage on server space i.e. CLOUD. The data owner uploads data on cloud space for increasing convenience and reduces the lot in organization of the data. The private data must be encrypting before outsource. The data which is being uploaded on cloud space is of supreme priority to enable the encryption of the data. Here the paper initiates the analysis about the similar approaches that are recently developed for cryptographic data retrieval from cloud. The system uses concept of TF-IDF model by which effective keywords are being extracted from text files that are repeatedly occurs, and their hashes get stored in Inverted Index. Thus the feature makes data accessible by searching through keywords, we propose model, by using SHA1 (Secure hash Algorithm) hash generation methodology, and DES (Data Encryption Standard) algorithm for the encryption of data. For the relevant retrieving of data from cloud, KNN (K-nearest neighbour) based searching is used. The proposed scheme achieves the identical security level by comparing the system with the existing ones and better performance. By doing this query complexity, functionality and the systems efficiency get improved.

Authors and Affiliations

Arpita Porwal
Department of Computer Science & Engineering, IES, IPS Academy, Indore, Madhya Pradesh, India
Deepak Shukla
Department of Computer Science & Engineering, IES, IPS Academy, Indore, Madhya Pradesh, India

Cloud Computing, Storage Infrastructure, Cryptographic Cloud, Secure Search, Keyword Based Search.

  1. Kahate, Atul, "Cryptography and Network Security", Tata McGraw-Hill ,India
  2. Xia Zhihua, and Xinhui Wang, 2016  IEEE  Transactions on Parallel and Distributed Systems, Pp- 340-352. ISSN No.- 1045-9219 DOI:10.1109/TPDS.2015.2401003
  3. Zhangjie Fu and Kui Ren, 2016,  IEEE Transactions on Information Forensics and Security.
  4. W. Sun et al.,2013, in Proc. 8th ASIACCS ,Privacy-preserving multi-keyword text search in the cloud supporting similarity-based ranking, Pp- 71–82.
  5. Ning Cao et al., 2014, IEEE Transactions on parallel and distributed systems, Privacy-preserving multi-keyword ranked search over encrypted cloud data, Pp- 222-233.
  6. Sumathi Sivaraj et al, 2014 International Journal of Computer Science and Mobile Computing, Vol.3 Issue.2, pg. 580-585
  7. Mayank Kudale et al., 2014, International Journal of Scientific Engineering and Technology Research , Pp: 1142-1145.
  8. Hongwei Li, Dongxiao Liu and  Xuemin, 2014, IEEE transaction on emerging topics in computing, Enabling Efficient Multi-Keyword Ranked Search Over Encrypted Mobile Cloud Data Through Blind Storage, DOI:10.1109/TETC.2014.2371239
  9. Li, Hongwei, et al. ,2015,  IEEE Transactions on Emerging Topics in Computing, Enabling efficient multi-keyword ranked search over encrypted mobile cloud data through blind storage, Pp-127-138.
  10. B. Wang, W. Song, W. Lou, and Y. T. Hou, 2015, in Proc. IEEE INFOCOM , Inverted index based multi-keyword public-key searchable encryption with strong privacy guarantee, Pp. 2092–2100.
  11. Li, Ruixuan, et al. 2014, Future Generation Computer Systems, Efficient multi-keyword ranked query over encrypted data in cloud computing,  Pp-179-190.

Publication Details

Published in : Volume 2 | Issue 4 | July-August 2017
Date of Publication : 2017-08-31
License:  This work is licensed under a Creative Commons Attribution 4.0 International License.
Page(s) : 880-885
Manuscript Number : CSEIT1724206
Publisher : Technoscience Academy

ISSN : 2456-3307

Cite This Article :

Arpita Porwal, Deepak Shukla, "Cryptographic Data Retrieval from Cloud by Hashing and Indexing Technique", International Journal of Scientific Research in Computer Science, Engineering and Information Technology (IJSRCSEIT), ISSN : 2456-3307, Volume 2, Issue 4, pp.880-885, July-August-2017.
Journal URL : http://ijsrcseit.com/CSEIT1724206

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