Conversely, Fuzzy Inference Systems can deal with the uncertainty of measures and control the outcomes more precisely therefore, a multilevel fuzzy inference system (HRA-MFIS) was proposed to replace the risk assessment model in HRA. The risk value is subjected to overestimation or underestimation since it is measured qualitatively, thus causing uncertainty problems, which was apparent in a previously proposed hybrid risk adaptive (HRA) access control system. Risk-based access control systems are part of identity management systems used to accommodate environments with needs for dynamic access control decisions. The experimental results show that the proposed multi-key model does, indeed, improve the overall security of the system while preserving the previous model architecture and with negligible processing overhead. Consequently, the proposed model helps in solving the issue of having a single point of failure caused by employing a master encryption key, as in the previous models. In this paper, the authors continue to improve on a previously proposed risk adaptive hybrid access control system, in which risk assessment is performed using a multilevel fuzzy inference system, by introducing an enhanced multi-key model for generating the symmetric encryption key dynamically for each user on demand. Accordingly, several studies have proposed risk-aware access control models to overcome the limitations of the traditional models. When studying traditional access control models, one could conclude that they have been proven inefficient in handling modern security threats, with access decisions influenced by several factors, including situational, environmental and risk factors.
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