Two-Phase Memetic Modifying Transformation for Solving the Task of Providing Group Anonymity

Chapter

Abstract

Nowadays, it has become a common practice to provide public access to various kinds of primary non-aggregated statistical data. Necessary precautions ought to be taken in order to guarantee that sensitive data features are masked, and data privacy cannot be violated. In the case of protecting information about a group of people, it is important to protect intrinsic data features and distributions. To do so, it is obligatory to introduce a certain level of distortion into the dataset. The problem of minimizing this distortion is a complex optimization task, which can be successfully solved by applying appropriate heuristic procedures, e.g., memetic algorithms. The task of determining whether a particular solution masks sensitive data features is an ill-defined one and often can be solved only by expert evaluation. In the paper, we propose to apply two-phase memetic algorithm to solve such tasks of providing group anonymity, for which it is not always possible to define appropriate constraints.

References

  1. 1.
    Brooks, D.: The Social Animal: The Hidden Sources of Love, Character, and Achievement. Random House Trade Paperbacks, New York (2011)Google Scholar
  2. 2.
    Aggarwal, C.C., Yu, P.S.: A general survey of privacy-preserving data mining: models and algorithms. In: Aggarwal, C.C., Yu, P.S. (eds.) Privacy-Preserving Data Mining: Models and Algorithms. Advanced in Database Systems, vol. 34, pp. 11–52. Springer Science+Business Media, LLC, New York (2008)Google Scholar
  3. 3.
    Fung, B., Wang, K., Chen, R., Yu, P.: Privacy-preserving data publishing: a survey of recent developments. ACM Comput. Surv. 42(4), 1–53 (2010)CrossRefGoogle Scholar
  4. 4.
    Sowmyarani, C.N., Srinivasan, G.N.: Survey on recent developments in privacy preserving models. Int. J. Comput. Appl. 38(9), 18–22 (2012)Google Scholar
  5. 5.
    Phitzmann, A., Hansen, M.: A terminology for talking about privacy by data minimization: anonymity, unlinkability, undetectability, unobservability, pseudonymity, and identity management. Version v0.34 [Online]. Available: http://dud.inf.tu-dresden.de/Anon_Terminology.shtml (2010)
  6. 6.
    Chertov, O., Pilipyuk, A.: Statistical disclosure control methods for microdata. In: 2009 International Symposium on Computing, Communication, and Control. Proceedings of CSIT, vol. 1, pp. 339–343. IACSIT Press, Singapore (2011)Google Scholar
  7. 7.
    Chertov, O. (ed.): Group Methods of Data Processing. Raleigh, Lulu.com (2010)MATHGoogle Scholar
  8. 8.
    Meyerson, A., Williams, R.: General k-anonymization is hard. Carnegie Mellon School of Computer Science, Technical Report, CMU-CS-03-113 (2003)Google Scholar
  9. 9.
    Moscato, P.: On evolution, search, optimization, genetic algorithms and martial arts: toward memetic algorithms. Caltech Concurrent Computation Program, Caltech, CA, C3P Report 826 (1989)Google Scholar
  10. 10.
    Eiben, A.E., Smith, J.E.: Introduction to Evolutionary Computing, 2nd edn. Springer, Berlin (2007)MATHGoogle Scholar
  11. 11.
    Dawkins, R.: The Selfish Gene: 30th Anniversary Edition. Oxford University Press, Oxford (2006)Google Scholar
  12. 12.
    Ray, T., Sarker, R.: Memetic algorithms in constrained optimization. In: Neri, F., Cotta, C., Moscato, P. (eds.) Handbook of Memetic Algorithms, pp. 135–151. Springer, Berlin (2012)CrossRefGoogle Scholar
  13. 13.
    Smith, A.E., Coit, D.W.: Penalty functions. In: Bäck, T., Fogel, D.B., Michalewicz, Z. (eds.) Evolutionary Computation 2. Advanced Algorithms and Operators, pp. 41–48. Institute of Physics Publishing, Bristol (2000)Google Scholar
  14. 14.
    Michalewicz, Z.: Repair algorithms. In: Bäck, T., Fogel, D.B., Michalewicz, Z. (eds.) Evolutionary Computation 2. Advanced Algorithms and Operators, pp. 56–61. Institute of Physics Publishing, Bristol (2000)Google Scholar
  15. 15.
    Michalewicz, Z.: Decoders. In: Bäck, T., Fogel, D.B., Michalewicz, Z. (eds.) Evolutionary Computation 2. Advanced Algorithms and Operators, pp. 49–55. Institute of Physics Publishing, Bristol (2000)Google Scholar
  16. 16.
    Chertov, O., Tavrov, D.: Providing group anonymity using wavelet transform. In: MacKinnon, L.M. (ed.) Data Security and Security Data, LNCS, vol. 6121, pp. 25–36. Springer, Berlin (2012)CrossRefGoogle Scholar
  17. 17.
    Tavrov, D., Chertov, O.: SSA-caterpillar in group anonymity. In: Presented at the World Conference in Soft Computing, San Francisco, CA (2011)Google Scholar
  18. 18.
    Chertov, O.R., Tavrov, D.Y.: Memetic algorithm for microfile modification with distortion minimization while providing group anonymity. Bull. Volodymyr Dahl East Ukrainian Nat. Univ. 8(179), 256–262 (2012). (in Ukrainian)Google Scholar
  19. 19.
    Chertov, O., Tavrov, D.: Memetic algorithm for solving the task of providing group anonymity. In: Jamshidi, M., Kreinovich, V., Kacprzyk, J. (eds.) Advanced Trends in Soft Computing. Studies in Fuzziness and Soft Computing, vol. 312, pp. 281–292. Springer, Switzerland (2014)Google Scholar
  20. 20.
    Goldberg, D.E., Korb, B., Deb, K.: Messy genetic algorithms: motivation, analysis, and first results. Complex Syst. 3, 493–530 (1989)MathSciNetMATHGoogle Scholar
  21. 21.
    U.S. Census 2000.: 5-percent public use microdata sample files [Online]. Available: http://www.census.gov/main/www/cen2000.html (2000)
  22. 22.
    Syswerda, G.: Schedule optimization using genetic algorithms. In: Davis, L. (ed.) Handbook of Genetic Algorithms, pp. 332–349. Van Nostrand Reinhold, New York (1991)Google Scholar
  23. 23.
    Brindle, A.: Genetic algorithms for function optimization. Doctoral dissertation, Department of Computer Science, Technical Report, TR81-2, University of Alberta (1981)Google Scholar
  24. 24.
    Goldberg, D.E.: Genetic Algorithms in Search, Optimization, and Machine Learning. Addison-Wesley, New York (1989)Google Scholar

Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  1. 1.Applied Mathematics DepartmentNational Technical University of Ukraine “Kyiv Polytechnic Institute”KievUkraine

Personalised recommendations