CFP last date
20 January 2025
Reseach Article

Discrimination Prevention using Privacy Preserving Techniques

by Asmita Kashid, Vrushali Kulkarni, Ruhi Patankar
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 120 - Number 1
Year of Publication: 2015
Authors: Asmita Kashid, Vrushali Kulkarni, Ruhi Patankar
10.5120/21195-3860

Asmita Kashid, Vrushali Kulkarni, Ruhi Patankar . Discrimination Prevention using Privacy Preserving Techniques. International Journal of Computer Applications. 120, 1 ( June 2015), 42-46. DOI=10.5120/21195-3860

@article{ 10.5120/21195-3860,
author = { Asmita Kashid, Vrushali Kulkarni, Ruhi Patankar },
title = { Discrimination Prevention using Privacy Preserving Techniques },
journal = { International Journal of Computer Applications },
issue_date = { June 2015 },
volume = { 120 },
number = { 1 },
month = { June },
year = { 2015 },
issn = { 0975-8887 },
pages = { 42-46 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume120/number1/21195-3860/ },
doi = { 10.5120/21195-3860 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T23:05:08.656138+05:30
%A Asmita Kashid
%A Vrushali Kulkarni
%A Ruhi Patankar
%T Discrimination Prevention using Privacy Preserving Techniques
%J International Journal of Computer Applications
%@ 0975-8887
%V 120
%N 1
%P 42-46
%D 2015
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Recently, it is observed that data mining technique may come across two problems- potential discrimination and potential privacy violation. Discrimination occurs as a result of use of discriminatory datasets for data mining tasks. Privacy violation occurs if a person's sensitive information is displayed to an unauthorized entity as a result of data mining tasks. Use of privacy preserving techniques to make data privacy protected can affect the amount of discrimination caused. It is important to study the relation of privacy and discrimination in the context of data mining. In this paper, we are trying to propose a method in which privacy preserving technique can be used to prevent discrimination and we can make the original data both privacy protected and discrimination-free.

References
  1. D. Pedreschi, S. Ruggieri, and F. Turini, "Discrimination-Aware Data Mining," Proc. 14th ACM Int'l Conf. Knowledge Discovery and Data Mining (KDD '08), pp. 560-568, 2008.
  2. S. Ruggieri, D. Pedreschi, and F. Turini, "Data Mining for Discrimination Discovery," ACM Trans. Knowledge Discovery from Data, vol. 4, no. 2, article 9, 2010.
  3. S. Hajian & J. Domingo-Ferrer, "A Methodology for Direct and Indirect Discrimination prevention in data mining," IEEE transaction on knowledge & data engg. pp. 1445-1459, July 2013.
  4. F. Kamiran and T. Calders, "Data preprocessing techniques for classification without discrimination," Intl' Journal of Knowledge & Information Systems, Springer, Vol. 33, no. 1, pp. 1-33, 2012.
  5. F. Kamiran, T. Calders, "Classifying without discriminating," In: Proceedings of IEEE IC4 international conference on computer, Control & Communication, pp. 1-6, 2009.
  6. F. Kamiran, T. Calders, and M. Pechenizkiy, "Discrimination Aware Decision Tree Learning," Proc. IEEE Int'l Conf. Data Mining (ICDM '10), pp. 869-874, 2010.
  7. T. Calders and S. Verwer, "Three Naive Bayes Approaches for Discrimination-Free Classification," Data Mining and Knowledge Discovery, vol. 21, no. 2, pp. 277-292, 2010.
  8. D. Pedreschi, S. Ruggieri and F. Turini, "Measuring Discrimination in Socially-Sensitive Decision Records," Proc. Ninth SIAM Data Mining Conf. (SDM '09), pp. 581-592, 2009.
  9. D. Pedreschi, S. Ruggieri and F. Turini, "Integrating Induction and Deduction for Finding Evidence of Discrimination", Proc. 12th ACM Int'l Conf. Artificial Intelligence and Law (ICAIL '09), pp. 157-166, 2009.
  10. S. Ruggieri, D. Pedreschi, and F. Turini, "DCUBE: Discrimination Discovery in Databases," Proc. ACM Int'l Conf. Management of Data (SIGMOD '10), pp. 1127-1130, 2010.
  11. B. Gao and B. Berendt, "Visual Data Mining for higher-level patterns: discrimination aware data mining and beyond," in Proc. 20th Benelearn, http://www. benelearn2011. org/, 2011.
  12. B. Berendt and S. Preibusch, "Exploring Discrimination: A user-centric evaluation of discrimination-aware data mining," in Proc. IEEE 12th Int'l Conf. on Data Mining Workshops (ICDMW), pp. 344-351, 2012.
  13. S. Hajian, J. Donimgo-Ferrer and Mart?´nez-Balleste´, "Discrimination Prevention in Data Mining for Intrusion and Crime Detection," Proc. IEEE Symp. Computational Intelligence in Cyber Security (CICS'11), pp. 47-54, 2011.
  14. A. Romei, S. Ruggieri and F. Turini, "Discovering gender discrimination in project funding," ICDM Workshops, pp. 394-401, 2012.
  15. G. Ristanoski, W. Liu, J. Bailey, "Discrimination Aware Classification for Imbalanced Dataset," Proc. 22nd ACM Int'l conference on information & knowledge management, pp. 1529-1532, 2013.
  16. I. Zliobaite, F. Kamiran, T. Calders, "Handling Conditional Discrimination," 11th IEEE International Conference on Data Mining, pp. 992-1001, 2011.
  17. T. Calders, A. Karim, F. Kamiran, W. Ali, and X. Zhang, "Controlling Attribute Effect in Linear Regression," Proc. IEEE 13th Int'l Conf. on Data Mining (ICDM), pp. 71-80, 2013.
  18. B. C. M Fung, K. Wang, R. Chen, P. S. Yu, "Privacy-preserving data publishing: A survey of recent developments," ACM Comput. Surv. 42(4), Article 14, 2010.
  19. S Hajian and J. Domingo-Ferrer, "A Study on the Impact of Data Anonymization on Anti-Discrimination," Proc. I. EEE 12th International Conference on Data Mining Workshops, pp. 352-359, 2012.
  20. S. Ruggieri, "Data Anonymity Meets Non-Discrimination," IEEE 13th International Conference on Data Mining Workshops (ICDMW), pp. 875-882, 2013.
  21. S. Hajian, A. Monreale, D. Pedreschi, J. Domingo-Ferrer and F. Ginnotti, "Injecting Discrimination and Privacy Awareness into Pattern Discovery," Proc. IEEE 12th International Conference on Data Mining Workshops, pp. 360-369, 2012.
  22. S. Hajian, A. Monreale, D. Pedreschi, J. Domingo-Ferrer and F. Ginnotti, "Fair Pattern Discovery," Proc. 29th Annual ACM Symposium on Applied Computing, pp. 113-120, 2014.
  23. S. Ruggieri, S. Hajian, F. Kamiran, and X. Zhang, "Anti-discrimination Analysis using Privacy Attack Strategies," Machine Learning and Knowledge Discovery in databases, Springer, pp. 694-710, 2014.
  24. Tiancheng Li, Ninghui Li, Jian Zhang, and Ian Molloy, "Slicing: A new approach for privacy preserving data publishing", IEEE transactions on knowledge and data engineering, Vol. 24, no. 3. 2012.
  25. D. J. Newman, S. Hettich, C. L. Blake, and C. J. Merz, "UCI Repository of Machine Learning Databases," http://archive. ics. uci. edu/ml, 1998.
Index Terms

Computer Science
Information Sciences

Keywords

Discrimination discovery discrimination prevention privacy preserving techniques