Research and Implementation of Access Control Strategy Based on Apriori and Collaborative Filtering Techniques

This paper presents an automated method for generating access control policies by combining the Apriori algorithm and collaborative filtering technology. This approach solves the complex access control challenges arising from data sharing and large number of users in power grid regulation systems. First, the Aprior algorithm is used to mine strong association rules from the user authority relationship to reveal the potential relationship between resources. Then, the user rights relationship is enhanced, resource similarity is calculated, and collaborative filtering is used to generate recommended values for unauthorized resources. Finally, the access control policy is classified and authorized according to the recommended value, and the automatic generation of the policy is realized. The experimental results show that this method can not only generate access control policies automatically, but also assign new permissions effectively and ensure the privacy of resource data.

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Publication Details

Published
2025-02-21
DOI
https://doi.org/10.1145/3728725.3728805
Primary Topic
Privacy-Preserving Technologies in Data
Type
article
Field-Weighted Citation Impact
0.00

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Controls
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article

Research and Implementation of Access Control Strategy Based on Apriori and Collaborative Filtering Techniques

Yujia Zhai, Minghui Jin, Feng Gao, Hongfu Chen
Privacy-Preserving Technologies in Data
article

Research and Implementation of Access Control Strategy Based on Apriori and Collaborative Filtering Techniques

Yujia Zhai, Minghui Jin, Feng Gao, Hongfu Chen
article en

Abstract

This paper presents an automated method for generating access control policies by combining the Apriori algorithm and collaborative filtering technology. This approach solves the complex access control challenges arising from data sharing and large number of users in power grid regulation systems. First, the Aprior algorithm is used to mine strong association rules from the user authority relationship to reveal the potential relationship between resources. Then, the user rights relationship is enhanced, resource similarity is calculated, and collaborative filtering is used to generate recommended values for unauthorized resources. Finally, the access control policy is classified and authorized according to the recommended value, and the automatic generation of the policy is realized. The experimental results show that this method can not only generate access control policies automatically, but also assign new permissions effectively and ensure the privacy of resource data.

Shanghai Electric (China) (CN)
Science and Technology Project of State Grid
Openalex Percentile: Top 94%
Privacy-Preserving Technologies in Data
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