The week's pick
Random Articles
Reseach Article
Sensitive Association Rule Hiding using Hybrid Algorithm in Incremental Environment
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 180 - Number 28 |
| Year of Publication: 2018 |
| Authors: Ankit Kharwar, Chandni Naik, Niyanta Desai, Nikita Mistree |
10.5120/ijca2018916650
|
Ankit Kharwar, Chandni Naik, Niyanta Desai, Nikita Mistree . Sensitive Association Rule Hiding using Hybrid Algorithm in Incremental Environment. International Journal of Computer Applications. 180, 28 ( Mar 2018), 5-9. DOI=10.5120/ijca2018916650
Abstract
Security of the huge database which includes certain sensitive information will become a vital issue when the data is released to outside world. Privacy preserving data mining is a new research area to protect privacy for sensitive information from exposé. PPDM include various association rules hiding method. The existing approach follows the concept of hiding the rule by fine tune the support of the LHS and RHS item of the rule. So the proposed approach is to combine the concept of ISL and DSR algorithms by manipulating the support of the LHS and RHS item of the rule and RHID is used to hide the rules for incremental environment. The advantage of combining this is to hide the rules from both sides in incremental environment. A novel approach for ARM using pattern generation is used instead of traditional apriori which reduce multiple database scan and require less memory space.
References
- Khyati B. Jadav,Jignesh Vania, Dhiren R. Patel, “A Survey on Association Rule Hiding Methods", International Journal of Computer Applications, ISSN: 09758887, Volume 82 No 13, November 2013.
- M. Atallah, E. Bertino, A. Elmagamind, M. Ibrahim, and V. S. Verykios \Disclo-sure limitation of sensitive rules",In Proc. of the 1999 IEEE Knowledge and Data Engineering Exchange Workshop (KDEX 1999), pp. 45-52.
- Sunil Kumar ,Mahaveer Singh, Nidhi Porwal, “An Algorithm for Hiding Association Rules on Data Mining", National Conference on Communication Technologies & its impact on Next Generation Computing CTNGC 2012 Proceedings publishedby International Journal of Computer Applications (IJCA)
- Vikash Shrivastava, Vivek Shrivastava, Vijay Patidar, A Generalized Association Rule Based Method for Privacy Preserving in Data Mining", International Journal of Advanced Research in Computer Science and Software Engineering, ISSN: 2277 128X, Volume 3, Issue 9, September 2013
- Kirtirajsinh Zala, Comparison of ISL, DSR, and New Variable Hiding Counter Algorithm of Association Rule Hiding", International Journal of Scienti_c & Engineering Research, ISSN 2229-5518, Volume 3, Issue 5, May-2012
- Chirag N. Modi,Udai Pratap Rao, Dhiren R. Patel, “Maintaining Privacy and Data Quality in Privacy Preserving Association Rule Mining", 2010 Second International conference on Computing, Communication and Networking Technologies
- V K S K Sai Vadapalli & G Loshma, “Secure Strategy for Privacy Preserving Association Rule Mining", International Conference on Computer Science and Engineering, April 28th, 2012, Vizag, ISBN: 978-93-81693-57-5
- Komal Shah, Amit Thakkar, Amit Ganatra, Association Rule Hiding by Heuristic Approach to Reduce Side E_ects & Hide Multiple R.H.S. Items", International Journal of Computer Applications, ISSN:0975 8887, Volume 45 No.1, May 2012.
- Nikunj H. Domadiya, Udai Pratap Rao, Hiding Sensitive Association Rules to Maintain Privacy and Data Quality in Database", 3rd IEEE International Advance Computing Conference (IACC) 2013
- Pratiksha Sapkal, Minakshi Panchal, Manisha Pol, Madhumita Mane, “Hiding Sensitive items using MDSRRC to Maintain Privacy in Database", Int. Journal of Engineering Research and Applications ISSN : 2248-9622, Vol. 4, Issue 2( Version 1), February 2014, pp.623-627
- Vikram Garg, Anju Singh, Divakar Singh, “A Hybrid Algorithm for Association Rule Hiding using Representative Rule", International Journal of Computer Applications, ISSN: 0975 8887, Volume 97 No.9, July 2014
- Frank, A. & Asuncion, A. (2010). UCI Machine Learning Repository [http://archive.ics.uci.edu/ml]. Irvine, CA: University of California, School of Information and Computer Science.
Index Terms
Keywords