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Privacy-Preserving Statistical Analysis Method for Real-World Data

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3 Author(s)
Ishii, J. ; NTT Network Innovation Labs., NTT Corp., Tokyo, Japan ; Maeomichi, H. ; Yoda, I.

We propose a method for obtaining statistical results such as averages, variances, and correlations without leaking any raw data values from data-holders by using multiple pseudonyms. At present, to obtain statistical results using a large amount of data, we need to collect all data in the same storage device. However, gathering real-world data that was generated by different people is not easy because they often contain private information. Thus, our method solves the problem and protects data-holders from data-user's malicious attacks. Finally, we evaluate the suitability of our method through implementation and experimentation.

Published in:

Trust, Security and Privacy in Computing and Communications (TrustCom), 2012 IEEE 11th International Conference on

Date of Conference:

25-27 June 2012