Abstract
The present disclosure describes an original and unique theoretical foundation, standard framework, model, and techniques for intelligent cloud authorization. The present disclosure provides for an original treatment to cloud authorization by topos generalization. The present disclosure sets up the theoretical foundation, develops the standard framework, and derives an inference-learn-deny model for intelligent cloud authorization. The present disclosure reinforces that topoi is an alternative universe in which homotopy analytics for intelligent cloud authorization is developed. The standardization derives two (co)monadic APIs for intelligent cloud authorization. The present disclosure characterizes intelligent cloud authorization in two different ways. First, the present disclosure develops the authorization frame by constructing a weak tree and an appropriate normalization procedure to encode minimal information by an n-graph for cloud authorization. Second, the present disclosure develops an artificial intelligence (AI) procedure to construct the authorization classifier in presence of uncertainty and additional information. Keywords associated with the present disclosure include: intelligent cloud authorization; cloud identity access management standards; topos generalization; inference-learn-deny model; homotopy analytics; APIs for intelligent cloud authorization; authorization frame; authorization classifier.
Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 License.
Recommended Citation
Liu, Lei, "A Homotopy-Theoretic Method for the Purpose of Intelligent Cloud Authorization", Technical Disclosure Commons, (November 12, 2018)
https://www.tdcommons.org/dpubs_series/1641