Have a personal or library account? Click to login
Hiding Sensitive High Utility and Frequent Itemsets Based on Constrained Intersection Lattice Cover

Hiding Sensitive High Utility and Frequent Itemsets Based on Constrained Intersection Lattice

Open Access
|Apr 2022

References

  1. 1. Agarwal, R., R. Srikant. Fast Algorithms for Mining Association Rules. – In: Proc. of 20th VLDB Conference, 1994. p. 499.
  2. 2. Agrawal, R., R. Srikant. Privacy-Preserving Data Mining. – In: Proc. of 2000 ACM SIGMOD International Conference on Management of Data, 2000, pp. 439-450.10.1145/335191.335438
  3. 3. Cheng, P., et al. Hide Association Rules with Fewer Side Effects. – IEICE TRANSACTIONS on Information, Vol. 98, 2015, No 10, pp. 1788-1798.10.1587/transinf.2014EDP7345
  4. 4. Fournier-Viger, P. 2021 [cited 2021 01/01/2021]. http://www.philippe-fournier-viger.com/spmf/index.php?link=datasets.php
  5. 5. Gan, W., et al. Privacy Preserving Utility Mining: A Survey. – In: Proc. of 2018 IEEE International Conference on Big Data (Big Data), 2018, IEEE, pp. 2617-2626.
  6. 6. GrCatzer, G. Lattice Theory: Foundation. 2011. Springer Science & Business Media.
  7. 7. Huynh Trieu, V., H. Le Quoc, C. Truong Ngoc. An Efficient Algorithm for Hiding Sensitive-High Utility Itemsets. – Intelligent Data Analysis, Vol. 24, 2020, No 4, pp. 831-845.10.3233/IDA-194697
  8. 8. Kiran, R. U., et al. Efficiently Finding High Utility-Frequent Itemsets Using Cutoff and Suffix Utility. – In: Proc. of Pacific-Asia Conference on Knowledge Discovery and Data Mining, 2019, Springer, pp. 191-203.10.1007/978-3-030-16145-3_15
  9. 9. Le, H. Q. et al. Association Rule Hiding in Risk Management for Retail Supply Chain Collaboration. – Computers in Industry, Vol. 64, 2013, No 7, pp. 776-784.10.1016/j.compind.2013.04.011
  10. 10. Lin, C.-W., et al. A GA-Based Approach to Hide Sensitive High Utility Itemsets. – The Scientific World Journal, Vol. 2014, 2014.10.1155/2014/804629396056824729755
  11. 11. Lin, J. C.-W., et al. Fast Algorithms for Hiding Sensitive High-Utility Itemsets in Privacy-Preserving Utility Mining. – Engineering Applications of Artificial Intelligence, Vol. 55, 2016, pp. 269-284.10.1016/j.engappai.2016.07.003
  12. 12. Liu, X., F. Xu, X. Lv. A Novel Approach for Hiding Sensitive Utility and Frequent Itemsets. – Intelligent Data Analysis, Vol. 22, 2018, No 6, pp. 1259-1278.10.3233/IDA-173613
  13. 13. Quoc Le, H., S. Arch-Int, N. Arch-Int. Association Rule Hiding Based on Intersection Lattice. – Mathematical Problems in Engineering, Vol. 2013, 2013.10.1155/2013/210405
  14. 14. Rajalaxmi, R., A. Natarajan. Effective Sanitization Approaches to Hide Sensitive Utility and Frequent Itemsets. – Intelligent Data Analysis, Vol. 16, 2012, No 6, pp. 933-951.10.3233/IDA-2012-00560
  15. 15. Yao, H., H. J. Hamilton, C. J. Butz. A Foundational Approach to Mining Itemset Utilities from Databases. – In: Proc. of 2004 SIAM International Conference on Data Mining, 2004. SIAM, pp. 482-486.10.1137/1.9781611972740.51
  16. 16. Yeh, J.-S., P.-C. Hsu. HHUIF and MSICF: Novel Algorithms for Privacy Preserving Utility Mining. – Expert Systems with Applications, Vol. 37, 2010, No 7, pp. 4779-4786.10.1016/j.eswa.2009.12.038
DOI: https://doi.org/10.2478/cait-2022-0001 | Journal eISSN: 1314-4081 | Journal ISSN: 1311-9702
Language: English
Page range: 3 - 23
Submitted on: May 11, 2021
Accepted on: Jan 11, 2022
Published on: Apr 10, 2022
Published by: Bulgarian Academy of Sciences, Institute of Information and Communication Technologies
In partnership with: Paradigm Publishing Services
Publication frequency: 4 issues per year

© 2022 Huynh Trieu Vy, Le Quoc Hai, Nguyen Thanh Long, Truong Ngoc Chau, Le Quoc Hieu, published by Bulgarian Academy of Sciences, Institute of Information and Communication Technologies
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.