TY - JOUR
T1 - Cooperative Classification under the Protection of PrivateInformation
AU - Lu Fang, Zhong Weijun and Zhang Yulin
JO - Journal of Information and Computing Science
VL - 4
SP - 283
EP - 289
PY - 2024
DA - 2024/01
SN - 4
DO - http://doi.org/
UR - https://global-sci.org/intro/article_detail/jics/22737.html
KW - TKeywords:T TPrivate Information, Enumerative Data, the Warner Model.  

AB - 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.