[IJCST-V4I2P17]:Prof. Harish Barapatre, Ms. Sampada Samel

February 28, 2018 | Penulis: EighthSenseGroup | Kategori: Statistical Classification, Data Mining, Privacy, Vertex (Graph Theory), Data
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Description: ABSTRACT Now a days, In our day to day life, development in data mining becomes very much popular. But, gr...

Deskripsi

ABSTRACT Now a days, In our day to day life, development in data mining becomes very much popular. But, growing popularity and development in data mining technologies brings serious threat to the security of individual’s sensitive information. So, To avoid access to one’s sensitive information, Privacy Preserving Data Mining (PPDM) is used. In this technique, data gets modified in order to secure one’s sensitive information. PPDM technique is mainly focused on how privacy maintained at Data Mining. However, Sensitive information can be retrieved at Data Collection, Data Publishing and Information Delivering processes. In this Paper, we briefly discuss the Privacy Preserving Data Mining with respect to user such as Data Provider, Data Collector, Data Miner and Decision Make. We will discuss privacy concerns related to each user. We also discuss about the Game Theory approaches. Keywords:- Data Mining, Privacy, information, KDD, PPDM, etc
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