Optimal object granularity determination method based on multi-granularity decision system

Abstract

The invention discloses an optimal object granularity determination method based on a multi-granularity decision system. The method comprises the following steps: A, judging whether a to-be-processedaccess control system is a newly built access control system or a to-be-optimized access control system; B, judging whether a consistent multi-granularity-level object granularity decision model is stored in a database or not; C, constructing a multi-granularity-level object granularity decision model; D, selecting the determined optimal object granularity according to the number of granularity layers in the constructed multi-granularity-layer object granularity selection model; E, calling the consistent multi-granularity-level object granularity decision model to perform reduction operation on an access object; F, respectively calculating a set of global optimal object granularity and local optimal object granularity of all objects, and then selecting the determined optimal object granularity according to the deviation ratio of the global optimal object granularity and the average value of the deviation ratio of the local optimal object granularity of all the objects. According to themethod, the confirmation process of the optimal object granularity can be simplified.

Description

technical field [0001] The invention relates to the field of optimal object granularity optimization in access control systems, in particular to a method for determining optimal object granularity based on a multi-granularity decision-making system. Background technique [0002] At present, the access granularity selection in the access control system is mainly divided into two aspects, one is the granularity selection of the role authority of the role-based access control model, and the other is the granularity selection of the access authority, and the granularity of the access authority is divided into object Granularity and operation granularity, the current access authority granularity selection is more focused on operation, how to select the object granularity of authority in the access control system has not seen much research. [0003] The selection of object granularity access rights in existing access control systems still relies on traditional experience. In the a...

AI Technical Summary

Problems solved by technology

This demand analysis process has defects such as long time period and high cost

Secondly, there is also a large degree of mismatch between the choice of permission granularity and the system requirements. On the one hand, because the requirements analysts are natural persons, they will make subjective mistakes; on the other hand, the needs of customers will change when the system is being developed.

Based on technical limitations, how to choose the optimal object access granularity in the access control system has not been studied much

[0004] The existing permission granularity selection method is relatively simple, and in the face of complex and changeable user needs, the subject has little choice in the access permission of the object

Excessive subject access rights will inadvertently lead to information leakage, and cannot effectively prevent Trojan attacks, resulting in poor flexibility

On the contrary, it will lead to the cumbersome authorization process of the access subject to the access object, and the implementation mechanism of the access operation is complicated

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