Clustering is a popular data processing strategy that attempts to partition data into related classes. It is especially crucial to defend the privacy of the database when the data comes from diverse sensors. Important factors that contribute to Cloud information security compliance has led to the rise of academics to restrict the leakage of cloud computing personal information. This paper proposes a k-means clustering algorithm for privacy protection In a cloud storage scope, to protect the privacy of users during clustering, which neither discloses personal privacy information nor leaks covariance matrix. Privacy-preserving cluster process computation is the main step in our privacy-preserving k-means. This paper proposes two privacy conservation protocols for cluster media computation. Our algorithm is being implemented by JAVA. It has extensively tested our privacy-preserving clustering algorithm on large data sets using our implementation. The safety and precision of our approach are verified by both theoretical framework and experimental outcomes.