JACLNet:Application of adaptive code length network in JavaScript malicious code detection

Currently, JavaScript malicious code detection methods are becoming more and more effective. Still, the existing methods based on deep learning are poor at detecting too long or too short JavaScript code. Based on this, this paper proposes an adaptive code length deep learning network JACLNet, compo...

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Detalles Bibliográficos
Autores principales: Zhang, Zhining, Wan, Liang, Chu, Kun, Li, Shusheng, Wei, Haodong, Tang, Lu
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2022
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9749972/
https://www.ncbi.nlm.nih.gov/pubmed/36516186
http://dx.doi.org/10.1371/journal.pone.0277891

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9749972/
https://www.ncbi.nlm.nih.gov/pubmed/36516186
http://dx.doi.org/10.1371/journal.pone.0277891

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