A Decision Tree Learning Approach for Mining Relationship-Based Access Control Policies
A Decision Tree Learning Approach for Mining Relationship-Based Access Control Policies
复制标题
挖掘基于关系的访问控制策略的决策树学习方法
DOI:
10.1145/3381991.3395619
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发表时间:
2020
期刊:
影响因子:
--
通讯作者:
Stoller, Scott D.
中科院分区:
文献类型:
--
作者:
Bui, Thang;Stoller, Scott D.
Relationship-based access control (ReBAC) provides a high level of expressiveness and flexibility that promotes security and information sharing, by allowing policies to be expressed in terms of chains of relationships between entities. ReBAC policy mining algorithms have the potential to significantly reduce the cost of migration from legacy access control systems to ReBAC, by partially automating the development of a ReBAC policy. This paper presents new algorithms, called DTRM (Decision Tree ReBAC Miner) and DTRM-, based on decision trees, for mining ReBAC policies from access control lists (ACLs) and information about entities. Compared to state-of-the-art ReBAC mining algorithms, our algorithms are significantly faster, achieve comparable policy quality, and can mine policies in a richer language.
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DOI:
10.1007/978-3-030-18419-3_18
发表时间:
2018
期刊:
Proceedings of the Eleventh ACM Conference on Data and Application Security and Privacy
影响因子:
--
作者:
Thang Bui;S. Stoller;Jiajie Li
通讯作者:
Jiajie Li
DOI:
10.1145/2818000.2818009
发表时间:
2015
期刊:
Proceedings of the 31st Annual Computer Security Applications Conference
影响因子:
--
作者:
J. Bogaerts;Maarten Decat;B. Lagaisse;W. Joosen
通讯作者:
W. Joosen
DOI:
10.1145/3322431.3325102
发表时间:
2019
期刊:
Proceedings of the 24th ACM Symposium on Access Control Models and Technologies
影响因子:
--
作者:
Nath, Ronit;Das, Saptarshi;Sural, Shamik;Vaidya, Jaideep;Atluri, Vijay
通讯作者:
Atluri, Vijay
影响因子:
5.6
作者:
Bui, Thang;Stoller, Scott D.;Li, Jiajie
通讯作者:
Li, Jiajie
DOI:
--
发表时间:
2013
期刊:
Symposium On Usable Privacy and Security
影响因子:
--
作者:
Matthias Beckerle;L. Martucci
通讯作者:
L. Martucci