Software Vulnerability Detection Using Deep Neural Networks: A Survey

The constantly increasing number of disclosed security vulnerabilities have become an important concern in the software industry and in the field of cybersecurity, suggesting that the current approaches for vulnerability detection demand further improvement. The booming of the open-source software c...

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Veröffentlicht in:	Proceedings of the IEEE Jg. 108; H. 10; S. 1825 - 1848
Hauptverfasser:	Lin, Guanjun, Wen, Sheng, Han, Qing-Long, Zhang, Jun, Xiang, Yang
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	New York IEEE 01.10.2020 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:	Artificial neural networks Computer bugs Computer security Cybersecurity Data mining Deep learning deep neural network (DNN) Feature extraction Literature reviews Machine learning machine learning (ML) Machine translation Neural networks Open source software representation learning Semantics Software engineering Software reliability software vulnerability Source code Speech recognition
ISSN:	0018-9219, 1558-2256
Online-Zugang:	Volltext
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