An Efficient Dynamic Multi-Keyword over Encrypted Cloud Storage

Authors(6) :-Abhishek Nimonkar, Mukul Wagh, Payal Kale, Pranali Bajirao, Yash Nathani, Prof. A.V. Dehankar

The approach of disseminated figuring, data proprietors are awakened to outsource their psyche boggling data organization systems from neighborhood goals to business open cloud for exceptional versatility and financial hold reserves. In any case, for guaranteeing data assurance, unstable data must be encoded before outsourcing, which obsoletes ordinary data use in perspective of plain text keyword look. In this way, engaging an encoded cloud data look for organization is of focal importance. Considering the broad number of data customers and reports in cloud, it is basic for the chase organization to allow multi-keyword question and give result similarity situating to meet the convincing data recuperation require. Related tackles searchable encryption focus on single keyword request or Boolean keyword look for, and on occasion isolate the question things. In this paper, curiously, we describe and handle the testing issue of assurance sparing multi-keyword situated investigate encoded cloud data (MRSE), and set up a game plan of strict insurance necessities for such a sheltered cloud data utilize system to wind up unmistakably a reality. Among various multi-keyword semantics, we pick the capable run of "organize planning", i.e., whatever number matches as could sensibly be normal, to get the similarity between interest request and data chronicles, and further use "inner thing likeness" to quantitatively formalize such rule for closeness estimation. We initially propose a central MRSE plot using secure inward thing figuring, and after that through and through upgrade it to meet differing insurance necessities in two levels of hazard models. Concentrated examination investigating security and adequacy confirmations of proposed arrangements is given, and examinations on this present reality dataset also show proposed plots without a doubt introduce low overhead on computation and correspondence.

Authors and Affiliations

Abhishek Nimonkar
BE Scholar, Department of Computer Technology, Priyadarshini College of Engineering, Nagpur, Maharashtra, India
Mukul Wagh
Assistant Professor, Department of Computer Technology, Priyadarshini College of Engineering, Nagpur, Maharashtra, India
Payal Kale

Pranali Bajirao

Yash Nathani

Prof. A.V. Dehankar

Cloud computing, Encryption, Inner product similarity, Single Keyword Search, Multi-keyword search, ranking.

  1. Qin Liuy, Guojun Wangyz, and Jie Wuz,”Secure and privacy preserving keyword searching for cloud storage services”, ELSEVIER Journal of Network and computer Applications, March 2011
  2. Ming Li et al.,” Authorized Private Keyword Search over Encrypted Data in Cloud Computing,IEEE proc. International conference on distributed computing systems, June 2011,pages 383-392
  3. Cong Wang et al.,”Enabling Secure and Efficient Ranked Keyword Search over Outsourced Cloud Data”, IEEE Transactions on parallel and distributed systems, vol. 23, no. 8, August 2012
  4. Kui Ren et al., “Towards Secure and Effective Data utilization in Public Cloud”, IEEE Transactions on Network, volume 26, Issue 6, November / December 2012
  5. Ming Li et al.,”Toward Privacy-Assured and Searchable Cloud Data Storage Services”, IEEE Transactions on Network, volume 27, Issue 4, July/August 2013
  6. Wei Zhou et al., “K-Gram Based Fuzzy Keyword Search over Encrypted Cloud Computing “Journal of Software Engineering and Applications, Scientific Research , Issue 6, Volume 29-32,January2013
  7. J. Baek et al., “Public key encryption with keyword search revisited", in ICCSA 2008, vol. 5072 of Lecture Notes in Computer Science, pp. 1249 - 1259, Perugia, Italy, 2008. Springer Berlin/Heidelberg.
  8. H. S. Rhee et al., “Trapdoor security in a searchable public-key encryption scheme with a designated tester," The Journal of Systems and Software, vol. 83, no. 5, pp. 763-771, 2010.
  9. Peng Xu et al., Public-Key Encryption with Fuzzy Keyword Search: A Provably Secure Scheme under Keyword Guessing Attack”,IEEE Transactions on computers, vol. 62, no. 11, November 2013
  10. Ning Cao et al.,” Privacy-Preserving Multi- Keyword Ranked Search over Encrypted Cloud Data”, IEEE Transactions on parallel and distributed systems, vol. 25, no. 1, jan 2014
  11. D. X. D. Song, D. Wagner, and A. Perrig, ”Practical techniques for searches on encrypted data,” in Proc. S & P, BERKELEY, CA, 2000, pp. 44.
  12. C. Wang, N. Cao, K. Ren, and W. J. Lou, Enabling Secure and Efficient Ranked Keyword Search over Outsourced Cloud Data, IEEE Trans. Parallel Distrib. Syst., vol. 23, no. 8, pp. 1467-1479, Aug. 2012.
  13. W. Sun, B. Wang, N. Cao, M. Li, W. Lou, Y. T. Hou, and H. Li, ”Privacy-preserving multi-keyword text search in the cloud supporting similarity-based ranking,” in Proc. ASIACCS, Hangzhou, China, 2013, pp. 71-82.
  14. R. X. Li, Z. Y. Xu, W. S. Kang, K. C. Yow, and C. Z. Xu, Efficient multi-keyword ranked query over encrypted data in cloud computing, Futur. Gener. Comp. Syst., vol. 30, pp. 179-190, Jan. 2014.
  15. Gurdeep Kaur, Poonam Nandal, “Ranking Algorithm of Web Documents using Ontology”, IOSR Journal of Computer Engineering (IOSR-JCE) eISSN: 2278-0661, p- ISSN: 2278-8727Volume 16, Issue 3, Ver. VIII (May-Jun. 2014), PP 52-55

Publication Details

Published in : Volume 6 | Issue 2 | March-April 2019
Date of Publication : 2019-04-30
License:  This work is licensed under a Creative Commons Attribution 4.0 International License.
Page(s) : 401-411
Manuscript Number : IJSRST196276
Publisher : Technoscience Academy

Print ISSN : 2395-6011, Online ISSN : 2395-602X

Cite This Article :

Abhishek Nimonkar, Mukul Wagh, Payal Kale, Pranali Bajirao, Yash Nathani, Prof. A.V. Dehankar, " An Efficient Dynamic Multi-Keyword over Encrypted Cloud Storage", International Journal of Scientific Research in Science and Technology(IJSRST), Print ISSN : 2395-6011, Online ISSN : 2395-602X, Volume 6, Issue 2, pp.401-411, March-April-2019.
Journal URL : https://ijsrst.com/IJSRST196276
Citation Detection and Elimination     |      | |
  • H. S. Rhee et al., “Trapdoor security in a searchable public-key encryption scheme with a designated tester," The Journal of Systems and Software, vol. 83, no. 5, pp. 763-771, 2010.
  • Peng Xu et al., Public-Key Encryption with Fuzzy Keyword Search: A Provably Secure Scheme under Keyword Guessing Attack”,IEEE Transactions on computers, vol. 62, no. 11, November 2013
  • Ning Cao et al.,” Privacy-Preserving Multi- Keyword Ranked Search over Encrypted Cloud Data”, IEEE Transactions on parallel and distributed systems, vol. 25, no. 1, jan 2014
  • D. X. D. Song, D. Wagner, and A. Perrig, ”Practical techniques for searches on encrypted data,” in Proc. S & P, BERKELEY, CA, 2000, pp. 44.
  • C. Wang, N. Cao, K. Ren, and W. J. Lou, Enabling Secure and Efficient Ranked Keyword Search over Outsourced Cloud Data, IEEE Trans. Parallel Distrib. Syst., vol. 23, no. 8, pp. 1467-1479, Aug. 2012.
  • W. Sun, B. Wang, N. Cao, M. Li, W. Lou, Y. T. Hou, and H. Li, ”Privacy-preserving multi-keyword text search in the cloud supporting similarity-based ranking,” in Proc. ASIACCS, Hangzhou, China, 2013, pp. 71-82.
  • R. X. Li, Z. Y. Xu, W. S. Kang, K. C. Yow, and C. Z. Xu, Efficient multi-keyword ranked query over encrypted data in cloud computing, Futur. Gener. Comp. Syst., vol. 30, pp. 179-190, Jan. 2014.
  • Gurdeep Kaur, Poonam Nandal, “Ranking Algorithm of Web Documents using Ontology”, IOSR Journal of Computer Engineering (IOSR-JCE) eISSN: 2278-0661, p- ISSN: 2278-8727Volume 16, Issue 3, Ver. VIII (May-Jun. 2014), PP 52-55
  • " target="_blank"> BibTeX
    |
  • H. S. Rhee et al., “Trapdoor security in a searchable public-key encryption scheme with a designated tester," The Journal of Systems and Software, vol. 83, no. 5, pp. 763-771, 2010.
  • Peng Xu et al., Public-Key Encryption with Fuzzy Keyword Search: A Provably Secure Scheme under Keyword Guessing Attack”,IEEE Transactions on computers, vol. 62, no. 11, November 2013
  • Ning Cao et al.,” Privacy-Preserving Multi- Keyword Ranked Search over Encrypted Cloud Data”, IEEE Transactions on parallel and distributed systems, vol. 25, no. 1, jan 2014
  • D. X. D. Song, D. Wagner, and A. Perrig, ”Practical techniques for searches on encrypted data,” in Proc. S & P, BERKELEY, CA, 2000, pp. 44.
  • C. Wang, N. Cao, K. Ren, and W. J. Lou, Enabling Secure and Efficient Ranked Keyword Search over Outsourced Cloud Data, IEEE Trans. Parallel Distrib. Syst., vol. 23, no. 8, pp. 1467-1479, Aug. 2012.
  • W. Sun, B. Wang, N. Cao, M. Li, W. Lou, Y. T. Hou, and H. Li, ”Privacy-preserving multi-keyword text search in the cloud supporting similarity-based ranking,” in Proc. ASIACCS, Hangzhou, China, 2013, pp. 71-82.
  • R. X. Li, Z. Y. Xu, W. S. Kang, K. C. Yow, and C. Z. Xu, Efficient multi-keyword ranked query over encrypted data in cloud computing, Futur. Gener. Comp. Syst., vol. 30, pp. 179-190, Jan. 2014.
  • Gurdeep Kaur, Poonam Nandal, “Ranking Algorithm of Web Documents using Ontology”, IOSR Journal of Computer Engineering (IOSR-JCE) eISSN: 2278-0661, p- ISSN: 2278-8727Volume 16, Issue 3, Ver. VIII (May-Jun. 2014), PP 52-55
  • " target="_blank">RIS
    |
  • H. S. Rhee et al., “Trapdoor security in a searchable public-key encryption scheme with a designated tester," The Journal of Systems and Software, vol. 83, no. 5, pp. 763-771, 2010.
  • Peng Xu et al., Public-Key Encryption with Fuzzy Keyword Search: A Provably Secure Scheme under Keyword Guessing Attack”,IEEE Transactions on computers, vol. 62, no. 11, November 2013
  • Ning Cao et al.,” Privacy-Preserving Multi- Keyword Ranked Search over Encrypted Cloud Data”, IEEE Transactions on parallel and distributed systems, vol. 25, no. 1, jan 2014
  • D. X. D. Song, D. Wagner, and A. Perrig, ”Practical techniques for searches on encrypted data,” in Proc. S & P, BERKELEY, CA, 2000, pp. 44.
  • C. Wang, N. Cao, K. Ren, and W. J. Lou, Enabling Secure and Efficient Ranked Keyword Search over Outsourced Cloud Data, IEEE Trans. Parallel Distrib. Syst., vol. 23, no. 8, pp. 1467-1479, Aug. 2012.
  • W. Sun, B. Wang, N. Cao, M. Li, W. Lou, Y. T. Hou, and H. Li, ”Privacy-preserving multi-keyword text search in the cloud supporting similarity-based ranking,” in Proc. ASIACCS, Hangzhou, China, 2013, pp. 71-82.
  • R. X. Li, Z. Y. Xu, W. S. Kang, K. C. Yow, and C. Z. Xu, Efficient multi-keyword ranked query over encrypted data in cloud computing, Futur. Gener. Comp. Syst., vol. 30, pp. 179-190, Jan. 2014.
  • Gurdeep Kaur, Poonam Nandal, “Ranking Algorithm of Web Documents using Ontology”, IOSR Journal of Computer Engineering (IOSR-JCE) eISSN: 2278-0661, p- ISSN: 2278-8727Volume 16, Issue 3, Ver. VIII (May-Jun. 2014), PP 52-55
  • " target="_blank">CSV

    Article Preview