A k-means clustering-based security framework for mobile data mining.

Data mining is a process of digging data sets from large data-bases, especially for use to improve the operation efficiency of a company, institution, or an organization. With the increasing cases of cyber and other computer-related crimes, computer and mobile data security has become a matter of concern, secure, and non-contaminated data is very important for data mining to improve the performance of a system. This paper proposes a system framework that is able to collect information and then be able to generate alerts in real time. The proposed scheme is then simulated using the K-means clustering algorithm, which is one of the most popular clustering algorithms to determine the efficiency and the accuracy of the proposed scheme. The paper concludes by proposing further improvements to be undertaken on the proposed system to improve its efficiency and accuracy. Copyright © 2017 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]