Toward Detection of Access Control Models from Source Code via Word Embedding

Proceedings of the 24th ACM Symposium on Access Control Models and Technologies, pp. 103-112, 2019.

Cited by: 1|Bibtex|Views22|DOI:https://doi.org/10.1145/3322431.3326329
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Other Links: dl.acm.org|academic.microsoft.com|dblp.uni-trier.de

Abstract:

Advancement in machine learning techniques in recent years has led to deep learning applications on source code. While there is little research available on the subject, the work that has been done shows great potential. We believe deep learning can be leveraged to obtain new insight into automated access control policy verification. In t...More

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