Compute Privacy Preserving Data Mining in a Cloud Computing Environment with Homomorphic Encryption

Compute Privacy Preserving Data Mining in a Cloud Computing Environment with Homomorphic Encryption

Supinder Kaur*, Rajveer kaur **, Parminder Singh ***

*Assistant Professor (Computer Science and Engineering, Rayat Bahra Institute of Engineering and Nano Technology, Email-id: supinder87kaur87@gmail.com)

**Assistant Professor (School of Engineering, Apeejay Institute of Management and Engineering Technical Campus, Email-id: rajveer216@gmail.com)

*** Assistant Professor (School of Computer Science and Engineering, Lovely Professional University, Email-id: Parminder.29695@lpu.co.in)

ABSTRACT

Cloud computing is the term used to describe an information technology infrastructure. Processing, in addition to software and data storage, takes place at a remote data center. Data centers for these fields are usually offered as a service over the internet existence of environments that are both large and complex, often accompanied by noise. Protecting privacy through the use of data mining approaches is equally crucial as well. Valuable sources should not be excluded while extracting frequent closed patterns. The ability to gather transaction-related information from any place is known as capability, which necessitates carrying out particular tasks. The proposed methodology in this paper aims to tackle the presented issue with a specific emphasis. In a distributed environment, the extraction of frequent closed patterns is integrated. We endeavor to maintain the confidentiality of site data, particularly when utilizing cloud technology. A mining task in a cloud environment using homomorphic encryption. Our mechanism requires, as indicated by the results of performance analysis and simulation. Reduced communication and computation costs can effectively attain data preservation. Data confidentiality is assured, data completeness is verified, and optimal transfer speeds are promoted.

Keywords: Cloud computing, Privacy, Data mining, Frequent closed patterns, Homomorphic encryption