1Research Scholar, Institute of Technology & Engineering, Nirma University, Ahmedabad, Gujarat, India
2Professor, Department of Computer Engineering, Institute of Technology & Engineering, Nirma University, Ahmedabad, Gujarat
3Associate Professor, Information & Communication Technology, Adani Institute of Infrastructure & Engineering, Ahmedabad, Gujarat, India
*(*Corresponding author) email id: *pmsolanki@gmail.com
Today's world entered into digital era. A huge number of data are generated at various government and public sectors, and they need to find out valuable information for futureuse from these dataset. So, data mining methods were advanced to analyse these dataset. The speedy advancement in the Internet and communications technology has led to the rise of data streams. Data stream mining methods are used to analyse data stream. Private data will be exposing while engaging in data analysis so privacy is major concern in terms of data analysis, validation and publishing. Privacy PreservingData Mining (PPDM) and Privacy Preserving Data Stream Mining (PPDSM) methods hide the sensitive data without disclosure and perform accurate mining result. Providing privacy with low information loss and better utility is the main goal of privacy preserving techniques. In recent years, PPDM and PPDSM have been studied broadly. In this paper, a comprehensive review of the PPDM and PPDSM methods is provided.
Data mining, Data stream mining, Privacy preserving, Clustering, Classification, Association
