TOWARDS EFFICIENT CRYPTOGRAPHY FOR PRIVACY PRESERVING DATA MINING IN DISTRIBUTED SYSTEMS

Emmanouil Magkos, Vassilis Chrissikopoulos

Abstract

A common fact for both businesses and physical entities is that sensitive, accurate information would be more easily diffused if adequate measures for protection were in place. This could also lead to higher quality data mining results, in a privacy preserving manner. Recent research has proved that it is possible to provide both privacy and accuracy assurances in a distributed computing scenario, where all participants may be mutually untrusted, without the presence of an unconditionally trusted third party. We believe that valuable knowledge can be borrowed from the vast body of literature on e-auction and e-voting systems, in order to be adapted to privacy preserving data mining systems in a distributed environment. These systems tend to balance well the efficiency and security criteria, because they need to be implementable in medium to large scale environments.

References

  1. Agrawal, R., Srikant, R., 2000. Privacy-preserving data ┬Áining. In ACM SIGMOD Conference on Management of Data. ACM Press, pp. 439-450.
  2. Anderson, R., 2001. Security engineering - A guide to building dependable distributed systems. Wiley Computer Publishing.
  3. Baudron, O., Fouque, P., Pointcheval, D., Poupard, G., Stern, J., 2001. Practical Multi-Candidate Election System. In 20th ACM Symposium on Principles of Distributed Computing. ACM Press, pp. 274-283.
  4. Chen, M., Han, J., Yu, P., 1996. Data mining: An overview from a database perspective. In IEEE Transactions on Knowledge and Data Engineering. IEEE Press, Vol. 8 (6), pp. 866-883.
  5. Cramer, R., Gennaro, R., Schoenmakers, B., 1997. A secure and optimally efficient multi-authority election scheme. In European Transactions on Telecommunications. Vol. 8 (5), pp. 481-490.
  6. Dunham, M., 2002. Data mining, introductory and advanced topics. Prentice Hall.
  7. Ferrer, J. (Ed.), 2002. Inference control in statistical databases, from theory to practice. Springer, LNCS Vol. 2316.
  8. Goldwasser, S., 1997. Multi-party computations: Past and present. In 16th Annual ACM Symposium on principles of Distributed Computing. ACM, pp. 1-6.
  9. Gritzalis, D. (Ed.), 2002. Secure electronic voting: trends and perspectives, capabilities and limitations. Kluwer Academic Publishers.
  10. Kantarcioglu, M., Clifton, C., 2004. Privacy-preserving distributed mining of association rules on horizontally partitioned data. In IEEE Transactions on Knowledge and Data Engineering. IEEE Press, Vol. 16 (9), pp. 1026-1037.
  11. Lindell, Y., Pinkas, B., 2000. Privacy preserving data mining. In Advances in Cryptology - CRYPTO 7800. Springer, LNCS Vol. 1880, pp. 36-53.
  12. Naor, M., Pinkas, B., Sumner, R., 1999. Privacy preserving auctions and mechanism design. In 1st ACM conference on Electronic commerce. ACM Press, pp. 129 - 139.
  13. Parkes, D., Rabin, M., Shieber, S., Thorpe, C., 2006. Practical secrecy-preserving, verifiably correct and trustworthy auctions. In 8th ACM International Conference on Electronic Commerce. ACM Press, pp. 70 - 81.
  14. Pinkas, B., 2002. Cryptographic techniques for privacypreserving data mining. In SIGKDD Explorations. ACM Press, Vol. 4(2), pp. 12-19.
  15. Schoenmakers, B., 1999. A Simple Publicly Verifiable Secret Sharing Scheme and Its Application to Electronic Voting. In Advances in CryptologyCRYPTO'99. Springer LNCS Vol. 1666. pp. 148-164.
  16. Vaidya, J., Clifton, C., 2002. Privacy preserving association rule mining in vertically partitioned data. In 8th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. ACM Press, pp. 639-644.
  17. Wang, J., Zhang, J., 2007. Addressing accuracy issues in privacy preserving data mining through matrix Factorization. In ISI'07, IEEE International Conference on Intelligence and Security Informatics. IEEE Press, pp. 217-220.
  18. Yang, Z., Zhong, S., Wright, R., 2005. Privacy-preserving classification of customer data without loss of accuracy. In SDM'05 SIAM Data Mining Conference.
  19. Yao, A., 1986. How to generate and exchange secrets. In 27th Symposium on Foundations of Computer Science. IEEE Press, pp. 162-167.
Download


Paper Citation


in Harvard Style

Magkos E. and Chrissikopoulos V. (2008). TOWARDS EFFICIENT CRYPTOGRAPHY FOR PRIVACY PRESERVING DATA MINING IN DISTRIBUTED SYSTEMS . In Proceedings of the Fourth International Conference on Web Information Systems and Technologies - Volume 1: WEBIST, ISBN 978-989-8111-26-5, pages 301-304. DOI: 10.5220/0001531403010304


in Bibtex Style

@conference{webist08,
author={Emmanouil Magkos and Vassilis Chrissikopoulos},
title={TOWARDS EFFICIENT CRYPTOGRAPHY FOR PRIVACY PRESERVING DATA MINING IN DISTRIBUTED SYSTEMS},
booktitle={Proceedings of the Fourth International Conference on Web Information Systems and Technologies - Volume 1: WEBIST,},
year={2008},
pages={301-304},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0001531403010304},
isbn={978-989-8111-26-5},
}


in EndNote Style

TY - CONF
JO - Proceedings of the Fourth International Conference on Web Information Systems and Technologies - Volume 1: WEBIST,
TI - TOWARDS EFFICIENT CRYPTOGRAPHY FOR PRIVACY PRESERVING DATA MINING IN DISTRIBUTED SYSTEMS
SN - 978-989-8111-26-5
AU - Magkos E.
AU - Chrissikopoulos V.
PY - 2008
SP - 301
EP - 304
DO - 10.5220/0001531403010304