CLUSTERING ROLE-BASED ACCESS CONTROL DATASET USING MODIFIED MACHINE LEARNING ALGORITHM
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One of the most popular access-control mechanisms is Role-based access control (RBAC) because it is convenience for the management and various security policies. Clustering is an unsupervised machine learning process that creates clusters such that data points inside a cluster share similar characteristics patterns. However, clustering is still a challenging task since many cluster algorithms fail to do well in scaling with the size of the data set and the number of dimensions that describe the points. The main aim of this project to study how to use the machine learning technique for clustering RBAC data set and modified it.
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"Learn about all the ways Walmart supports nonprofit organizations.
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