• jyoti srivastava
• shefali rana
• jigisha patel

Data mining is a process of extracting the large database, these databases are mostly scattered among various websites where security is required. These databases are divided into various categories such as horizontally distributed databases, vertically distributed databases and hybrid distributed databases. Privacy concept occurs when the data is distributed in environment and association rule also depend on the distribution of data in environment. Privacy preserving data mining (PPDM) is most important in data security field and it has become serious concern in the secure transformation of personal data. Association rule mining (ARM) algorithms are used to discover important knowledge from databases. There are Some problem in secure mining when transactions are vertically distributed. Each site holds some attributes of each transaction, and sites wish to collaborate. Various algorithms have been designed for it. In this paper, summarize them and survey of current algorithms, and analyse the mining methods for vertical distributed database.

Distributed database, Privacy Preserving Data Mining, Association Rule Mining

"A Survey Paper on Secure Mining for Vertical Distributed Database", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.6, Issue 4, page no.433-438, April-2019, Available :http://www.jetir.org/papers/JETIR1904777.pdf

"A Survey Paper on Secure Mining for Vertical Distributed Database", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.6, Issue 4, page no. pp433-438, April-2019, Available at : http://www.jetir.org/papers/JETIR1904777.pdf