Skip to main content
SpringerLink
Log in

Association Rule Hiding Using Firefly Optimization Algorithm

  • Conference paper
  • First Online:
Intelligent Systems Design and Applications (ISDA 2018 2018)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 941))

Abstract

Privacy preserving data mining is an important research area which protects the private information and reduces the information loss during the data mining process. There are many data mining techniques whereas Association rule mining is one of the data mining technique which finds existing correlations between data items. Privacy Preserving Association Rule Mining is one of the techniques in this field, which aims to hide sensitive association rules. Many different algorithms with particular approaches have been developed to protect the private information. In this paper, a new approach has been introduced using firefly optimization algorithm for hiding the sensitive association rules. To hide the sensitive rules distortion technique was used. Further in this work fitness function was defined to achieve the optimal solution with fewest side effects. The efficiency of proposed algorithm was evaluated with different databases. The results of the execution of the proposed algorithm and existing algorithm tabu search on different databases indicates that firefly algorithm has better performance compared to other algorithm.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 169.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 219.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Agarwal, C.C., Yu, P.S. (eds.): Privacy-Preserving Data Mining: Modeland Algorithms (2008). ISBN 0-387-70991-8

    Google Scholar 

  2. Jain, Y.K.: An efficient association rule hiding algorithm for privacy-preserving data mining. Int. J. Comput. Sci. Eng. 3(7), 2792–2798 (2011)

    Google Scholar 

  3. Nayak, G., Devi, S.: A survey on privacy preserving data mining: approaches and techniques. Int. J. Eng. Sci. Technol. 3(3), 2127–2133 (2011)

    Google Scholar 

  4. Patel Tushar, S., Mayur, P., Dhara, L., Jahnvi, K., Piyusha, D., Ashish, P., Reecha, P.: Association an analytical study of various frequent itemset mining algorithms. Res. J. Comput. Inf. Technol. Sci. 1(1), 6–9 (2013). February Res. J. Computer & IT Sci. International Science Congress

    Google Scholar 

  5. Han, J., Kamber, M., Pei, J.: Data Mining: Concepts and Techniques. Morgan Kaufmann, San Mateo (2006)

    MATH  Google Scholar 

  6. Saygin, Y., Verykios, V.S., Elmagarmid, A.K.: Privacy preserving association rule mining. In: Proceedings of the 2002 International (2002)

    Google Scholar 

  7. Schuster, A., Wolff, R., Gilburd, B.: Privacy preserving data mining on data grids in the presence of malicious participants. In: IEEE International Symposium on High Performance Distributed Computing - HPDC (2004)

    Google Scholar 

  8. Zhang, N., Wang, S., Zhao, W.: A new scheme on privacy preserving association rule mining. In: Principles of Data Mining and Knowledge Discovery – PKDD, vol. 3202, pp. 484–495 (2004)

    Google Scholar 

  9. Otey, M.E., Wang, C., Parthasarathy, S., Veloso, A., Meria, W.: Mining frequent itemsets in distributed and dynamic databases. In: IEEE International Conference on Data Mining (2003)

    Google Scholar 

  10. Afshari, M.H., Dehkordi, M.N., Akbari, M.: Association rule hiding using cuckoo optimization algorithm. Expert Syst. Appl. 64, 340–351 (2016)

    Article  Google Scholar 

  11. Dehkordi, M.N., Badie, K., Zadeh, A.K.: A novel method for privacy preserving in association rule mining based on genetic algorithms. J. Softw. 4(6), 555–562 (2009)

    Google Scholar 

  12. Yang, X.S.: A discrete firefly algorithm for the multi-objective hybrid flow shop scheduling problems. IEEE Trans. Evol. Comput. 18(2), 301–305 (2014)

    Google Scholar 

  13. Jia, D., Duan, X., Khan, M.K.: Binary artificial bee colony optimization using bitwise operation. Comput. Ind. Eng. 76, 360–365 (2014)

    Article  Google Scholar 

  14. Khan, A., Qureshi, M.S., Hussain, A.: Improved genetic algorithm approach for sensitive association rules hiding. World Appl. Sci. J. 31(12), 2087–2092 (2014)

    Google Scholar 

  15. Le, H.Q., Arch-Int, S., Nguyen, H.X., Arch-Int, N.: Association rule hiding in risk management for retail supply chain collaboration. Comput. Ind. 64(7), 776–784 (2013)

    Article  Google Scholar 

  16. Oliveira, S.R.M., Zaiane, O.R.: Privacy preserving frequent itemset mining. In: Proceedings of the IEEE International Conference on Privacy, Security and Data Mining, vol. 14, pp. 43–54 (2002)

    Google Scholar 

  17. Vijayarani, S., Tamilarasi, A., SeethaLakshmi, R.: Tabu search based association rule hiding. Int. J. Comput. Appl. 19(1), 0975–8887 (2011)

    Google Scholar 

  18. Yuan, F., Chen, S., Liu, H.: Association rules mining on heart failure differential treatment based on the improved firefly algorithm. J. Comput. 9(4), 822–830 (2014)

    Google Scholar 

  19. Neelima, S., Sathyanarayan, N., Murthy, P.K.: A novel multi-objective firefly algorithm for optimization of association rule mining (2017)

    Google Scholar 

  20. Telikani, A., Shahbahrami, A.: Data sanitization in association rule mining: an analytical review. Expert Syst. 96, 406–426 (2017)

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Computer Science, Bharathiar University, Coimbatore, India

    S. Sharmila & S. Vijayarani

Authors
  1. S. Sharmila
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. S. Vijayarani
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to S. Sharmila .

Editor information

Editors and Affiliations

  1. Machine Intelligence Research Labs, Auburn, WA, USA

    Ajith Abraham

  2. School of Information Technology and Engineering, Vellore Institute of Technology, Vellore, Tamil Nadu, India

    Aswani Kumar Cherukuri

  3. Tijuana Institute of Technology, Tijuana, Mexico

    Patricia Melin

  4. Machine Intelligence Research Labs, Auburn, WA, USA

    Niketa Gandhi

Rights and permissions

Reprints and permissions

Copyright information

© 2020 Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Sharmila, S., Vijayarani, S. (2020). Association Rule Hiding Using Firefly Optimization Algorithm. In: Abraham, A., Cherukuri, A., Melin, P., Gandhi, N. (eds) Intelligent Systems Design and Applications. ISDA 2018 2018. Advances in Intelligent Systems and Computing, vol 941. Springer, Cham. https://doi.org/10.1007/978-3-030-16660-1_68

Download citation

Publish with us

Policies and ethics

Search

Navigation