分布式隐私保护数据采掘中一种基于椭圆曲线密码的高安全传输框架
A Novel Framework using Elliptic Curve Cryptography for Extremely Secure Transmission in Distributed Privacy Preserving Data Mining
摘要：
隐私保护数据采掘是一种在挖掘过程中确保个人信息隐私的方法。最重要的任务是从分布的多个数据库中检索信息。数据一旦进入数据仓库，就可以被挖掘算法用来检索机密信息。建议的框架有两个主要任务，安全传输和保密信息在采矿过程中。安全传输是通过使用椭圆曲线密码和数据失真的隐私保护，确保高度安全的环境。
英文摘要：
Privacy Preserving Data Mining is a method which ensures privacy of individual information during mining. Most important task involves retrieving information from multiple data bases which is distributed. The data once in the data warehouse can be used by mining algorithms to retrieve confidential information. The proposed framework has two major tasks, secure transmission and privacy of confidential information during mining. Secure transmission is handled by using elliptic curve cryptography and data distortion for privacy preservation ensuring highly secure environment.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
