A Metaheuristic Algorithm for Hiding Sensitive Itemsets

  • Jerry Chun-Wei LinEmail author
  • Yuyu Zhang
  • Philippe Fournier-Viger
  • Youcef Djenouri
  • Ji Zhang
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11030)


In this paper, we first present a multi-objective algorithm for hiding the sensitive information with transaction deletion based on the NSGAII framework. The proposed can efficiently sort the non-dominated solutions and find the set of Pareto results for later process. Experimental results on two real datasets illustrated that the proposed algorithm can achieve satisfactory results with fewer side effects compared to the previous single-objective evolutionary approaches.


PPDM Sanitization Evolutionary computation Pareto solutions 



This research was partially supported by the Shenzhen Technical Project under JCYJ20170307151733005 and KQJSCX20170726103424709.


  1. 1.
    Atallah, M., Bertino, E., Elmagarmid, A., Ibrahim, M., Verykios, V.: Disclosure limitation of sensitive rules. Workshop Knowl. Data Eng. Exch. 29, 45–52 (1999)Google Scholar
  2. 2.
    Agrawal, R., Srikant, R.: Privacy-preserving data mining. ACM SIGMOD Rec. 29(2), 439–450 (2000)CrossRefGoogle Scholar
  3. 3.
    Clifton, C., Kantarcioglu, M., Vaidya, J., Lin, X., Zhu, M.Y.: Tools for privacy preserving distributed data mining. ACM SIGKDD Explor. 4, 1–7 (2003)Google Scholar
  4. 4.
    Chen, P., Lee, I., Lin, C.W., Pan, J.S.: Association rule hiding based on evolutionary multi-objective optimization. Intell. Data Anal. 20(3), 495–514 (2016)CrossRefGoogle Scholar
  5. 5.
    Deb, K., Agrawal, S., Pratap, A., Meyarivan, T.: A fast elitist non-dominated sorting genetic algorithm for multi-objective optimization: NSGA-II. In: Schoenauer, M., et al. (eds.) PPSN 2000. LNCS, vol. 1917, pp. 849–858. Springer, Heidelberg (2000). Scholar
  6. 6.
    Dasseni, E., Verykios, V.S., Elmagarmid, A.K., Bertino, E.: Hiding association rules by using confidence and support. In: Moskowitz, I.S. (ed.) IH 2001. LNCS, vol. 2137, pp. 369–383. Springer, Heidelberg (2001). Scholar
  7. 7.
    Fournier-Viger, P., et al.: The SPMF open-source data mining library version 2. In: Berendt, B., et al. (eds.) ECML PKDD 2016. LNCS (LNAI), vol. 9853, pp. 36–40. Springer, Cham (2016). Scholar
  8. 8.
    Fournier-Viger, P., Lin, J.C.W., Kiran, R.U., Koh, Y.S., Thomas, R.: A survey of sequential pattern mining. Data Sci. Pattern Recogn. 1(1), 54–77 (2017)Google Scholar
  9. 9.
    Gan, W., Lin, J.C.W., Fournier-Viger, P., Chao, H. C., Tseng, V.S., Yu, P.S.: A survey of utility-oriented pattern mining. arXiv:1805.10511 (2018)
  10. 10.
    Gan, W., Lin, J.C.W., Fournier-Viger, P., Chao, H. C., Yu, P. S.: A survey of parallel sequential pattern mining. arXiv:1805.10515 (2018)
  11. 11.
    Holland, J.: Adaptation in Natural and Artificial Systems: An Introductory Analysis with Applications to Biology, Control and Artificial Intelligence. MIT Press, Cambridge (1992)Google Scholar
  12. 12.
    Han, S., Ng, W.K.: Privacy-preserving genetic algorithms for rule discovery. In: Song, I.Y., Eder, J., Nguyen, T.M. (eds.) DaWaK 2007. LNCS, vol. 4654, pp. 407–417. Springer, Heidelberg (2007). Scholar
  13. 13.
    Kennedy, J., Eberhart, R.: Particle swarm optimization. In: IEEE International Conference on Neural Networks, pp. 1942–1948 (1995)Google Scholar
  14. 14.
    Knowles, J., Corne, D.: The pareto archived evolution strategy: a new baseline algorithm for pareto multiobjective optimisation. In: The Congress on Evolutionary Computation, pp. 98–105 (1999)Google Scholar
  15. 15.
    Lindell, Y., Pinkas, B.: Privacy preserving data mining. In: The Annual International Cryptology Conference on Advances in Cryptology, pp. 36–54 (2000)Google Scholar
  16. 16.
    Lin, C.W., Zhang, B., Yang, K.T., Hong, T.P.: Efficiently hiding sensitive itemsets with transaction deletion based on genetic algorithms. Sci. World J. 2014, 13 (2014). Article ID 398269Google Scholar
  17. 17.
    Lin, C.W., Hong, T.P., Yang, K.T., Wang, S.L.: The GA-based algorithms for optimizing hiding sensitive itemsets through transaction deletion. Appl. Intell. 42(2), 210–230 (2015)CrossRefGoogle Scholar
  18. 18.
    Lin, J.C.W., Liu, Q., Fournier-Viger, P.: A sanitization approach for hiding sensitive itemsets based on particle swarm optimization. Eng. Appl. Artif. Intell. 53, 1–18 (2016)CrossRefGoogle Scholar
  19. 19.
    Marco, D., Sabrina, O., Thomas, S.: Ant colony optimization. IEEE Comput. Intell. Mag. 1(4), 28–39 (2004)Google Scholar
  20. 20.
    Oliveira, S.R.M., Zaïane, O.R.: Privacy preserving frequent itemset mining. In: IEEE International Conference on Privacy, Security and Data Mining, pp. 43–54 (2002)Google Scholar
  21. 21.
    Storn, R., Price, K.: Differential evolution-a simple and efficient heuristic for global optimization over continuous spaces. J. Glob. Optim. 11(4), 341–359 (1997)MathSciNetCrossRefGoogle Scholar
  22. 22.
    Schaffer, J.D.: Multiple objective optimization with vector evaluated genetic algorithms. In: International Conference on Genetic Algorithms, vol. 2, no. 1, pp. 93–100 (1985)Google Scholar
  23. 23.
    Srinivas, N., Deb, K.: Multiobjective optimization using nondominated sorting in genetic algorithms. Evol. Comput. 2(3), 221–248 (1994)CrossRefGoogle Scholar
  24. 24.
    Verykios, V.S., Bertino, E., Fovino, I.N., Provenza, L.P., Saygin, Y., Theodoridis, Y.: State-of-the-art in privacy preserving data mining. ACM SIGMOD Rec. 33, 50–57 (2004)CrossRefGoogle Scholar
  25. 25.
    Zitzler, E., Thiele, L.: Multiobjective evolutionary algorithms: a comparative case study and the strength Pareto approach. IEEE Trans. Evol. Comput. 3(4), 257–271 (1999)CrossRefGoogle Scholar

Copyright information

© Springer Nature Switzerland AG 2018

Authors and Affiliations

  • Jerry Chun-Wei Lin
    • 1
    • 2
    Email author
  • Yuyu Zhang
    • 1
  • Philippe Fournier-Viger
    • 3
  • Youcef Djenouri
    • 4
  • Ji Zhang
    • 5
  1. 1.School of Computer Science and TechnologyHarbin Institute of Technology, ShenzhenShenzhenChina
  2. 2.Department of Computing, Mathematics, and PhysicsWestern Norway University of Applied Sciences (HVL)BergenNorway
  3. 3.School of Natural Sciences and HumanitiesHarbin Institute of Technology, ShenzhenShenzhenChina
  4. 4.IMADASouthern Denmark UniversityOdenseDenmark
  5. 5.University of Southern QueenslandToowoombaAustralia

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