A New Scheme to Privacy-Preserving Collaborative Data Mining

摘要：

Protection of privacy has become an important problem in data mining. In this paper, we present a new scheme to privacy-preserving collaborative data mining based on the homomorphic encryption and ElGamal encryption system in distributed environment. This scheme can be used to compute the k-nearest neighbor search. Our scheme is provable secure and efficient and can prevent colluded attacker. Comparing with the previous work on this issue, our method can be used in multi-parties who want to cooperatively compute the answers without revealing to each other their identity and their private data.

关键词： Security and privacy data mining privacy-preserving data mining k-nearest neighbor classification

作者: Jianming Zhu

作者单位: School of Information,Central University of Finance and Economics,Beijing,China

会议类型: 国际会议

会议名称: The Fifth International Conference on Information Assurance and Security(第五届信息保障与安全国际会议)

会议地点: 西安

会议语种:英文

页码: 468-471

在线出版日期: 2009-08-18（万方平台首次上网日期，不代表论文的发表时间）