Toward Deep Learning Based Access Control-Reference-Cited by-同舟云学术

Toward Deep Learning Based Access Control

Published:2022-04-14 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the Twelfth ACM Conference on Data and Application Security and Privacy
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Author:

Nobi Mohammad Nur¹,Krishnan Ram¹,Huang Yufei²,Shakarami Mehrnoosh¹,Sandhu Ravi¹

Affiliation:

1. University of Texas at San Antonio, San Antonio, TX, USA

2. University of Pittsburgh & UPMC Hillman Cancer Center, Pittsburgh, PA, USA

Funder

NSF Division of Computer and Network Systems (CNS)

National Science Foundation (NSF)

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3508398.3511497

Reference77 articles.

1. Manar Alohaly Hassan Takabi and Eduardo Blanco. 2018. A deep learning approach for extracting attributes of ABAC policies. In SACMAT. ACM. Manar Alohaly Hassan Takabi and Eduardo Blanco. 2018. A deep learning approach for extracting attributes of ABAC policies. In SACMAT. ACM.

2. Kaggle Amazon. 2013. Amazon Employee Access Challenge in Kaggle. https://www.kaggle.com/c/amazon-employee-access-challenge/ Kaggle Amazon. 2013. Amazon Employee Access Challenge in Kaggle. https://www.kaggle.com/c/amazon-employee-access-challenge/

3. UCI Amazon. 2011. Amazon Access Samples Data Set. http://archive.ics.uci.edu/ml/datasets/Amazon UCI Amazon. 2011. Amazon Access Samples Data Set. http://archive.ics.uci.edu/ml/datasets/Amazon

4. Access Access

5. Samples Samples

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