Obfuscated Mobile Malware Detection by Means of Dynamic Analysis and Explainable Deep Learning-Reference-Cited by-同舟云学术

Obfuscated Mobile Malware Detection by Means of Dynamic Analysis and Explainable Deep Learning

Published:2023-08-29 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 18th International Conference on Availability, Reliability and Security
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Author:

Mercaldo Francesco¹^ORCID,Ciaramella Giovanni²^ORCID,Santone Antonella³^ORCID,Martinelli Fabio²^ORCID

Affiliation:

1. University of Molise & IIT-CNR, Italy

2. IIT-CNR, Italy

3. University of Molise, Italy

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3600160.3605037

Reference24 articles.

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3. Gerardo Canfora , Andrea Di Sorbo , Francesco Mercaldo , and Corrado Aaron Visaggio . 2015. Obfuscation techniques against signature-based detection: a case study. In 2015 Mobile systems technologies workshop (MST) . IEEE , 21–26. Gerardo Canfora, Andrea Di Sorbo, Francesco Mercaldo, and Corrado Aaron Visaggio. 2015. Obfuscation techniques against signature-based detection: a case study. In 2015 Mobile systems technologies workshop (MST). IEEE, 21–26.

4. Metamorphic Malware Detection Using Code Metrics

5. Dynamic Mobile Malware Detection through System Call-based Image representation.J;Casolare Rosangela;Wirel. Mob. Networks Ubiquitous Comput. Dependable Appl.,2021