Author:
Rani Nanda,Mishra Ayushi,Kumar Rahul,Ghosh Sarbajit,Shukla Sandeep K.,Bagade Priyanka
Publisher
Springer Nature Switzerland
Reference19 articles.
1. Lecture Notes in Computer Science;A Singh,2019
2. Dhavlle, A., Shukla, S.: A novel malware detection mechanism based on features extracted from converted malware binary images, ArXiv, vol. abs/2104.06652 (2021)
3. Prajapati, P., Stamp, M.: An empirical analysis of image-based learning techniques for malware classification. In: Stamp, M., Alazab, M., Shalaginov, A. (eds.) Malware Analysis Using Artificial Intelligence and Deep Learning. Springer, Cham (2021). https://doi.org/10.1007/978-3-030-62582-5_16
4. Kim, J.Y., Cho, S.B.: Obfuscated malware detection using deep generative model based on global/local features. Comput. Secur. 112, 102501 (2022). ISSN 0167-4048. https://doi.org/10.1016/j.cose.2021.102501
5. Bozkir, A., Tahillioglu, E., Aydos, M., Kara, I.: Catch them alive: a malware detection approach through memory forensics, manifold learning and computer vision. Comput. Secur. 103, 04 (2021)
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