Privacy Preserving Approaches for Global Cycle Detections for Cyclic Association Rules in Distributed Databases

Nirali R. Nanavati, Devesh C. Jinwala

Abstract

The current massive proliferation of data has led to collaborative data mining that requires preservation of individual privacy of the participants. A number of algorithms proposed till date in this scenario are limited to mining association rules and do not consider their cyclic nature that finds associations with respect to the time segment. Hence catering to this challenge, we propose techniques for privacy preservation while finding global cycles when mining cyclic association rules in a distributed setup. The proposed techniques are based on homomorphic encryption and Shamir’s secret sharing that can help us decipher partial and total global cycles along with maintaining privacy in a distributed setup. Additionally security, efficiency and correctness analysis of the proposed algorithms are also given.

References

  1. Aggarwal, C. C. and Yu, P. S., (2008). A general survey of privacy-preserving data mining models and algorithms. In Privacy-Preserving Data Mining, volume 34 of The Kluwer International Series on Advances in Database Systems, pages 11-52. Springer US.
  2. Ben Ahmed, E. and Gouider, M. S., (2010). Towards a new mechanism of extracting cyclic association rules based on partition aspect. In Research Challenges in Information Science (RCIS), 2010 Fourth Interna tional Conference on, pages 69 -78.
  3. Freedman, M. J., Nissim, K., and Pinkas, B., (2004). Efficient private matching and set intersection. Pages 1-19. Springer-Verlag.
  4. Ge, X., Yan, L., Zhu, J., and Shi, W., (2010). Privacy preserving distributed association rule mining based on the secret sharing technique. In Software Engineer ing and Data Mining (SEDM), 2010 2nd International Conference on, pages 345 -350.
  5. Kantarcioglu, M., (2008). A Survey of Privacy-Preserving Methods Across Horizontally Partitioned Data. In Privacy-Preserving Data Mining, volume 34 of Advances in Database Systems, pages 313-335. Springer US.
  6. Kantarcioglu, M. and Clifton, C., (2004). Privacy preserving distributed mining of association rules on horizontally partitioned data. Knowledge and Data Engineering, IEEE Transactions on, 16(9):1026 1037.
  7. Kargupta, H., Das, K., and Liu, K., (2007). Multi-party, privacy-preserving distributed data mining using a game theoretic framework. In Proceedings of the 11th European conference on Principles and Practice of Knowledge Discovery in Databases, PKDD 2007, pages 523-531, Berlin, Heidelberg. Springer-Verlag.
  8. Ozden, B., Ramaswamy, S., and Silberschatz, A. (1998). Cyclic association rules. In Proceedings of the Fourteenth International Conference on Data Engineering, ICDE 7898, pages 412-421, Washington, DC, USA. IEEE Computer Society.
  9. Pedersen, T. B., Saygin, Y., and Savas, E. (2007). Secret Sharing vs. Encryption-based Techniques For Privacy Preserving Data Mining. Sciences-New York, (December):17-19.
  10. Sang, Y., Shen, H., and Tian, H., (2009). Privacy preserving tuple matching in distributed databases. IEEE Trans. on Knowl. and Data Eng., 21:1767-1782.
  11. Shamir, A., (1979). How to share a secret. Commun. ACM, 22:612-613.
  12. Shi, E., Chan, T.-H. H., Rieffel, E. G., Chow, R., and Song, D., (2011). Privacy-preserving aggregation of timeseries data. In NDSS.
  13. Vaidya, J. (2008). A survey of privacy-preserving methods across vertically partitioned data.
  14. Venkatadri.Mand Reddy, D. L. C., (2011). Article: A review on data mining from past to the future. International Journal of Computer Applications, 15(7):19-22.
Download


Paper Citation


in Harvard Style

R. Nanavati N. and C. Jinwala D. (2012). Privacy Preserving Approaches for Global Cycle Detections for Cyclic Association Rules in Distributed Databases . In Proceedings of the International Conference on Security and Cryptography - Volume 1: SECRYPT, (ICETE 2012) ISBN 978-989-8565-24-2, pages 368-371. DOI: 10.5220/0004018803680371


in Bibtex Style

@conference{secrypt12,
author={Nirali R. Nanavati and Devesh C. Jinwala},
title={Privacy Preserving Approaches for Global Cycle Detections for Cyclic Association Rules in Distributed Databases},
booktitle={Proceedings of the International Conference on Security and Cryptography - Volume 1: SECRYPT, (ICETE 2012)},
year={2012},
pages={368-371},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004018803680371},
isbn={978-989-8565-24-2},
}


in EndNote Style

TY - CONF
JO - Proceedings of the International Conference on Security and Cryptography - Volume 1: SECRYPT, (ICETE 2012)
TI - Privacy Preserving Approaches for Global Cycle Detections for Cyclic Association Rules in Distributed Databases
SN - 978-989-8565-24-2
AU - R. Nanavati N.
AU - C. Jinwala D.
PY - 2012
SP - 368
EP - 371
DO - 10.5220/0004018803680371