Security Analyze Outsourced Association Rule Mining on Vertically Partitioned Databases

Authors(2) :-Bade Ankammarao, Shaik Aseff

Data Analysis techniques that are Association manage mining and Frequent thing set mining are two prominent and broadly utilized for different applications. The conventional framework concentrated independently on vertically parceled database and on a level plane apportioned databases on the premise of this presenting a framework which concentrate on both on a level plane and vertically divided databases cooperatively with protection safeguarding component. Information proprietors need to know the continuous thing sets or affiliation rules from an aggregate information set and unveil or uncover as few data about their crude information as could reasonably be expected to other information proprietors and outsiders. To guarantee information protection a Symmetric Encryption Technique is utilized to show signs of improvement result. Cloud supported successive thing set mining arrangement used to exhibit an affiliation govern mining arrangement. The subsequent arrangements are intended for outsourced databases that permit various information proprietors to proficiently share their information safely without trading off on information protection. Information security is one of the key procedures in outsourcing information to different outside clients. Customarily Fast Distribution Mining calculation was proposed for securing conveyed information. These business locales an issue by secure affiliation governs over parceled information in both even and vertical. A Frequent thing sets calculation and Distributed affiliation administer digging calculation is used for doing above method adequately in divided information, which incorporates administrations of the information in outsourcing process for disseminated databases. This work keeps up or keeps up proficient security over vertical and flat perspective of representation in secure mining applications.

Authors and Affiliations

Bade Ankammarao
Department of MCA , St. Mary's Group of Institutions, Guntur, Andhra Pradesh, India
Shaik Aseff
Department of MCA , St. Mary's Group of Institutions, Guntur, Andhra Pradesh, India

Association rules mining, frequent item set mining, privacy-preserving data mining, partitioned data

  1. Lichun Li, Rongxing Lu, Kim-Kwang Raymond Choo, Anwitaman Datta, and Jun Shao, -Privacy Preserving-Outsourced Association Rule Mining on Vertically Partitioned
  2. Databases IEEE Transactions on Information Forensics and Security, Vol. 11, No. 8, August 2016.
  3. J. Vaidya and C. Clifton, -Privacy preserving association rule mining in vertically partitioned data, in Proc. SIGKDD, 2002, pp. 639–644.
  4. B. Rozenberg and E. Gudes, -Association rules mining in vertically partitioned databases, Data Knowl. Eng., vol. 59, no. 2, pp. 378–396.
  5. S. Zhong, Privacy-preserving algorithms for distributed mining of frequent itemsets, Inf. Sci., vol. 177, no. 2, pp. 490–503.
  6. F. Giannotti, L. V. S. Lakshmanan, A. Monreale, D. Pedreschi, and H. Wang, -Privacy-preserving mining of association rules from outsourced transaction databases, IEEE Syst. J., vol. 7, no. 3, pp. 385–395,Sep. 2013.
  7. W.  K.  Wong,  D.  W.  Cheung,  E.  Hung,  B.  Kao,  and  N.
  8. Mamoulis,-Security in outsourcing of association rule mining, in Proc. VLDB,2007, pp. 111–122.
  9. J. Lai, Y. Li, R. H. Deng, J. Weng, C. Guan, and Q. Yan, -Towards semantically secure outsourcing of association rule mining on categorical data, Inf. Sci., vol. 267, pp. 267–286, May 2014.
  10. M. Kantarcioglu and C. Clifton, -Privacy-preserving distributed mining of association rules on horizontally partitioned data, IEEE transactions on knowledge and data engineering, vol. 16, no. 9, pp. 1026-1037.
  11. O.  Goldreich,  -Encryption  schemes,  working  draft,  (2003) March.
  12. H.   Grosskreutz,   B.   Lemmen   and   S.   Rüping,   -Secure
  13. Distributed Subgroup Discovery in Horizontally Partitioned Data, Transactions on Data Privacy, vol. 4 no. 3, (2011), pp. 147-165.
  14. Can Xiang, Chunming Tang -Efficient outsourcing schemes of modular exponentiations with checkability for untrusted cloud server J Ambient Intell Human Comput (2015) 6:131–139.
  15. Xinjing Ge, Li Yan, Jianming Zhu, Wenjie Shi -Privacy-Preserving Distributed Association Rule Mining Based on the Secret Sharing Technique, 2009 IEEE.
  16. Xuan Canh Nguyen, Hoai Bac Le, Tung Anh Cao -An enhanced scheme for privacy-preserving association rules mining on horizontally distributed databases 978-1-4673-0309-5/12, 2012 IEEE
  17. Mahmoud Hussein, Ashraf El-Sisi, Nabil Ismail, -Fast Cryptographic Privacy Preserving Association Rules Mining on
  18. Distributed Homogenous DataBase, Knowledge-Based Intelligent Information and Engineering Systems, Lecture Notes in Computer Science, Volume 5178/2008, pp. 607 - 616 (2008).
  19. Moez Waddey , Pascal Poncelet, Sadok Ben Yahia, Novel Approach For Privacy Mining Of Generic Basic Association Rules,In PAVLAD’09, November 6, 2009, Hong Kong, China, 2009 ACM.
  20. J. Vaidya, Clifton. -Privacy preserving association rule mining in vertically partitioned data - In: Proceedings of the Eighth
  21. N. V. Muthu Lakshmi1 & K. Sandhya Rani, -Privacy Preserving Association Rule Mining in Vertically Partitioned Databases, In International Journal of Computer Applications (0975 – 8887) Volume 39– No.13, February 2012.
  22. Zhu Yu- quan, Tang Yang, Chen Geng, -A Privacy Preserving Algorithm for Mining Distributed Association Rules, 19-21 May 2011.
  23. Boxiang Dong, Ruilin Liu, and Hui (Wendy) Wang -Trust-but-Verify: Verifying Result Correctness of Outsourced Frequent Itemset Mining in Data-Mining-As-a-Service Paradigm IEEE Transactions On Services Computing, Vol. 9, No. 1, January/February 2016.
  24. Md. Golam Kaosar, Russell Paulet, Xun Yi -Optimized Two Party Privacy Preserving Association Rule Mining Using Fully Homomorphic Encryption Springer 2011.
  25. Kaingade, Rasika M., and Hemant A. Tirmare. "Personalization of Web Search based on privacy protected and auto-constructed user profile." Advances in Computing, Communications and Informatics (ICACCI), 2015 International Conference on. IEEE, 2015.
  26. Parkar, Mr Vishal Vijaykumar. "Enhancing Security Audit for Web Applications with Dynamic Modeling Approach." (2016)

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) : 441-446
Manuscript Number : CSEIT1724104
Publisher : Technoscience Academy

ISSN : 2456-3307

Cite This Article :

Bade Ankammarao, Shaik Aseff, "Security Analyze Outsourced Association Rule Mining on Vertically Partitioned Databases", International Journal of Scientific Research in Computer Science, Engineering and Information Technology (IJSRCSEIT), ISSN : 2456-3307, Volume 2, Issue 4, pp.441-446, July-August-2017.
Journal URL : http://ijsrcseit.com/CSEIT1724104

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