• Abishek M John
• Subin Omanakuttan

In this modern world, storing of data is a major issue. Terabytes and terabytes of data are produced every day. This rapidly increasing data is called big data. These extremely large or complex data sets cannot be handled by a traditional data processing application. One of the best solutions for this problem is to use a cloud system. Cloud Computing offers a number of benefits and services to its customers who pay for the use of hardware and software resources (servers hosted in data centers, applications, software...) on demand which they can access via the internet without the need for expensive computers or a large storage system capacity and without paying any equipment maintenance fees. But there is the main issue of data security and privacy while storing the big data on the cloud. A major issue in Data Mining based attacks is the entry of an unauthorized user to extract valuable information by analyzing the raw data. This paper proposes an efficient technique for securely mining the data by means of k-means clustering and using Homomorphic encryption for extra security of data in a cloud system. In this process flow, the cloud server is unaware of data uploaded by the user and the client only gets the computational results. Through experimental evaluation, we can maintain the correctness and confidentiality of the final result.

Cloud Computing, Security, K-means, Datamining,Encryption

"Efficient Knowledge Discovery In Cloud Using K-Means Clustering And Homomorphic Encryption", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.6, Issue 6, page no.567-571, June 2019, Available :http://www.jetir.org/papers/JETIR1906P81.pdf

"Efficient Knowledge Discovery In Cloud Using K-Means Clustering And Homomorphic Encryption", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.6, Issue 6, page no. pp567-571, June 2019, Available at : http://www.jetir.org/papers/JETIR1906P81.pdf