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Providing group anonymity as a part of CSID data process

Chertov O.1, Tavrov D.2
1 National Technical University of Ukraine «Igor Sikorsky Kyiv Polytechnic Institute»
2 National Technical University of Ukraine “Kyiv Polytechnic Institute”

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UDC: 004.62:004.023
Publication Language: Ukrainian
Stuc. intelekt. 2017; 22(3-4):127-138

Abstract: In the article, the task of providing group anonymity is discussed in the context of the CSID data process. A comparative study of appropriate methods given in the literature is performed. Based on this study, conditions are formulated for choosing methods that fit each particular case.

Keywords: group anonymity, CSID data process, memetic algorithm, microfile

References:

  1. Duncan G.T. Exploring the tension between privacy and the social benefits of governmental databases / G.T. Duncan // Little Knowledge: Privacy, Security, and Public Information after September 11 [eds. J. Podesta, P.M. Shane, R.C.A. Leone]. — The Century Foundation : New York, 2004. — P. 71–88.
  2. Duncan G.T. Statistical Confidentiality. Principles and Practice / G.T. Duncan, M. Elliot, G.J.J. Salazar. — New York : Springer-Verlag, 2011. — 212 p.
  3. Gehrke J. Privacy in Data Publishing / J. Gehrke, D. Kifer, A. Machanavajjhala // IEEE 29th International Conference on Data Engineering (ICDE). — 2010. — P. 1213.
  4. Little R.J.A. Statistical Analysis of Masked Data / R.J.A. Little // Journal of Official Statistics. — 1993. — 9(2). — P. 407–426.
  5. A Terminology for Talking About Privacy by Data Minimization: Anonymity, Unlinkability, Undetectability, Unobservability, Pseudonymity, and Identity Management, Version v0.34 [Electronic resource] / A. Pfitzmann, M. Hansen. — 2010. — Mode of access: http://dud.inf.tu- dresden.de/Anon_Terminology.shtml
  6. Evfimievski A. Randomization in Privacy Preserving Data Mining / A. Evfimievski // ACM SIGKDD Explorations Newsletter. — ACM Press, 2002. — 4(2). — P. 43–48.
  7. Sweeney L. k-anonymity: a model for protecting privacy / L. Sweeney // International Journal on Un- certainty, Fuzziness and Knowledge-Based Systems. — World Scientific, 2002. — 10(5). — P. 557–570.
  8. Fienberg S. Data Swapping: Variations on a Theme by Dalenius and Reiss / S. Fienberg, J. McIntyre // Journal of Official Statistics. — 2005. — Vol. 21(2). — P. 309–324.
  9. Domingo-Ferrer J. A survey of inference control methods for privacy-preserving data mining / J. Domingo- Ferrer // Privacy-Preserving Data Mining: Models and Algorithms. — Springer, 2008. — P. 53–80.
  10. Parmar A.A. Blocking based approach for classification rule hiding to preserve the privacy in database / A.A. Parmar, U.P. Rao, D.R. Patel // International Symposium on Computer Science and Society. — 2011. — P. 323–326.
  11. Liu Q. A Privacy-Preserving Data Publishing Method for Multiple Numerical Sensitive Attributes via Clust. and Multi-Sens. Bucket. / Q. Liu, H. Shen, Y. Sang // Int. Symp. on Par. Arch., Alg. and Progr. — 2014. — P. 220–223.
  12. Singh A. Privacy preserving techniques in social networks data publishing-a review / A. Singh, D. Bansal, S. Sofat // International Journal of Computer Applications. — 2014. — Vol. 87, No. 15. — P. 9–14.
  13. Rashid A.H. Privacy-preserving data publishing: review / A.H. Rashid, N.B.M. Yasin // International Journal of Physical Sciences. — 2015. — Vol. 10(7). — P. 239–247.
  14. Tavrov D.Y. Dvofazovyi memetychnyi alhorytm zabezpechennia hrupovoii anonimnosti danykh / D.Y. Tavrov, O.R. Chertov // Shtuchnyi Intelekt. — 2015. — No 1–2. — S. 170–179.
  15. Chertov O. Microfiles as a Potential Source of Confidential Information Leakage / O. Chertov, D. Tavrov // Intelligent Methods for Cyber Warfare [ed. R.R. Yager, M.Z. Reformat, N. Alajlan]. — Springer International Publishing Switzerland, 2015. — P. 87–114.
  16. Chertov O. Memetic Algorithm for Solving the Task of Providing Group Anonymity / O. Chertov, D. Tavrov // Advance Trends in Soft Computing [ed. M. Jamshidi, V. Kreinovich, J. Kacprzyk]. — Springer International Publishing Switzerland, 2014. — P. 281–292.
  17. Chertov O. Two-Phase Memetic Modifying Transformation for Solving the Task of Providing Group Anonymity / O. Chertov, D. Tavrov // Recent Developments and New Direction in Soft-Computing Foundations and Applications [eds. L.A. Zadeh, A.M. Abbasov, R.R. Yager, S.N. Shahbazova, M.Z. Reformat]. — Springer International Publishing Switzerland, 2016. — P. 239–253.
  18. Kleinberg J. Algorithm Design / J. Kleinberg, E. Tardos. — Pearson, 2005. — 864 p.
  19. Liu L. Wavelet-Based Data Perturbation for Simultaneous Privacy-Preserving and Statistics-Preserving / L. Liu, J. Wang, J. Zhang // 2008 IEEE International Conference on Data Mining Workshops. — IEEE Computer Society Press, 2008. — P. 27–35.
  20. Chertov O. Providing Group Anonymity Using Wavelet Transform / O. Chertov, D. Tavrov // Data Security and Security Data [ed. L.M. MacKinnon]. — Berlin, Heidelberg : Springer-Verlag, 2012. — P. 25–36.
  21. Golyandina N. The “Caterpillar”-SSA Method for Analysis of Time Series with Missing Values / N. Golyandina, E. Osipov // Journal of Statistical Planning and Inference. — 2007. — Vol. 137(8). — P. 2642–2653.
  22. Neri F. A Primer on Memetic Algorithms / F. Neri, C. Cotta // Handbook of Memetic Algorithms [eds. F. Neri, C. Cotta, P. Moscato]. — Berlin, Heidelberg : Springer-Verlag, 2012. — P. 43–52.

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