@Article{JICS-4-283, author = {Lu Fang, Zhong Weijun and Zhang Yulin}, title = {Cooperative Classification under the Protection of PrivateInformation}, journal = {Journal of Information and Computing Science}, year = {2024}, volume = {4}, number = {4}, pages = {283--289}, abstract = {TAbstract.T The private information of enterprises is a bottleneck to enterprises’ cooperation. Enterprises often analyze cooperatively their consumers’ information, but laws and their image require enterprises to protect consumers’ information. To resolve the conflict between information-sharing and information- protecting, a privacy preserving classification method with distributed private information is proposed. We uses the Warner model to hide the true private enumerative data of enterprises’ consumers information. Then we introduces how to get the exact classifying result on the disturbed data and analyze the method’s accuracy and privacy in theory. In the end, the method’s feasibility and validity is proved by experiments. }, issn = {1746-7659}, doi = {https://doi.org/}, url = {http://global-sci.org/intro/article_detail/jics/22737.html} }