Antivirus applied to JAR malware detection based on runtime behaviors

Java vulnerabilities correspond to 91% of all exploits observed on the worldwide web. The present work aims to create antivirus software with machine learning and artificial intelligence and master in Java malware detection. Within the proposed methodology, the suspected JAR sample is executed to in...

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Detalles Bibliográficos
Autores principales: Pinheiro, Ricardo P., Lima, Sidney M. L., Souza, Danilo M., Silva, Sthéfano H. M. T., Lopes, Petrônio G., de Lima, Rafael D. T., de Oliveira, Jemerson R., Monteiro, Thyago de A., Fernandes, Sérgio M. M., Albuquerque, Edison de Q., Silva, Washington W. A. da, Santos, Wellington P. dos
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2022
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8817023/
https://www.ncbi.nlm.nih.gov/pubmed/35121776
http://dx.doi.org/10.1038/s41598-022-05921-5

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8817023/
https://www.ncbi.nlm.nih.gov/pubmed/35121776
http://dx.doi.org/10.1038/s41598-022-05921-5

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