期刊名称：International Journal of Computer Technology and Applications
电子版ISSN：2229-6093
出版年度：2013
卷号：4
期号：6
页码：973-975
出版社：Technopark Publications
摘要：The competing parties who have private data may collaboratively conduct privacy preserving distributed data analysis (PPDA) tasks to learn beneficial data models or analysis results. For example, different credit card companies may try to build better models for credit card fraud detection through PPDA tasks. Similarly, competing companies in the same industry may try to combine their sales data to build models that may predict the future sales. In many of these cases, the competing parties have different incentives. Although certain PPDA techniques guarantee that nothing other than the final analysis result is revealed, it is impossible to verify whether or not participating parties are truthful about their private input data
