首页    期刊浏览 2024年11月08日 星期五
登录注册

文章基本信息

  • 标题:Analysis of Privacy Preserving in Data Mining
  • 本地全文:下载
  • 作者:DharmikVasiyani ; Hiral Desai ; Jay Gandhi
  • 期刊名称:International Journal of Innovative Research in Computer and Communication Engineering
  • 印刷版ISSN:2320-9798
  • 电子版ISSN:2320-9801
  • 出版年度:2015
  • 卷号:3
  • 期号:9
  • DOI:10.15680/IJIRCCE.2015. 0309089
  • 出版社:S&S Publications
  • 摘要:Here provides an overview of the new and rapidly emerging research area of privacy preserving datamining. It becomes more popular because it allows you to share your private data for analysis purpose. SometimesEnterprise needs to share their data to gain mutual benefit with collaboration to the other enterprise data. Thiscollaboration may cause attack on shared private data. So to privacy preserving on those data are necessary. Here giventhe overview of the privacy preserving in data mining with its techniques and different algorithms and itsapplications.Also here include latest challenges in this field and also describe that in future work we can apply Ldiversityanonymity along with clustering to reduce information loss. There are few efforts are given regarding thisapproach and they all used different clustering approach to get good utility in anonymity.
  • 关键词:Data mining; Privacy Preserving;Cryptography; Association Rules;Classification; Clustering.
国家哲学社会科学文献中心版权所有