Study on Privacy Preserving Data Mining

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Study on Data Mining from Private Database of Questionnaires.We have studied the issue of disclosures of private evaluation from web-based questionnaire and clarified that the potential souse of disclosures is malicious insiders who engaged into administrative tasks of public server. In order to prevent dishonest behavior of malicious parties, we have applied a new cryptographical protocol of secure function evaluation using homomorphic public-key algorithms. The conventional protocol of secure function evaluation, however, can not apply here because a variety of question styles other than a simple one-out-of-n style are used in currently applied questionnaire survey. Thus, we have developed a new protocol based on disjunctive zero-knowledge proof protocol to overcome the issue of complicated style of questions. The performance and security of the proposed scheme are investigated in J.Nakazato and H.Kikuchi, Security Enhancement Preventing Personal Information Disclosure in Web-Based Questionnaire, IPSJ Journal, Vol.46, No.8, pp.2068-2077, 2005.We have also studied other data-mining algorithm including decision tree learning based on entropy, clustering schemes using Euclid distance and uncertain reasoning. One application is to automated web page classification systems with subjective uncertainty. Some of these schemes can be used to give a new protocol of extracting watermark information without revealing secret keys. We have shown several issues such as accuracy and performance of these protocols.