Access Control Role Evolution Mechanism for Open Computing Environment

Aodi Liu, Xuehui Du, Na Wang
<span title="2020-03-21">2020</span> <i title="MDPI AG"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/ikdpfme5h5egvnwtvvtjrnntyy" style="color: black;">Electronics</a> </i> &nbsp;
Data resources in open computing environments (including big data, internet of things and cloud computing) are characterized by large scale, wide source, and strong dynamics. Therefore, the user-permission relationship of open computing environments has a huge scale and will be dynamically adjusted over time, which enables effective permission management in the role based access control (RBAC) model to become a challenging problem. In this paper, we design an evolution mechanism of access
more &raquo; ... l roles for open computing environments. The mechanism utilizes the existing user-permission relationship in the current system to mine the access control role and generate the user-role and role-permission relationship. When the user-permission relationship changes, the roles are constantly tuned and evolved to provide role support for access control of open computing environments. We propose a novel genetic-based role evolution algorithm that can effectively mine and optimize roles while preserving the core permissions of the system. In addition, a role relationship aggregation algorithm is proposed to realize the clustering of roles, which provides a supplementary reference for the security administrator to give the role real semantic information. Experimental evaluations in real-world data sets show that the proposed mechanism is effective and reliable.
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.3390/electronics9030517">doi:10.3390/electronics9030517</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/rih3fd4rm5h7xddza6kqa7zgyu">fatcat:rih3fd4rm5h7xddza6kqa7zgyu</a> </span>
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