Malware detection using convolutional neural network
Vecchiarelli, Daniele (A.A. 2022/2023) Malware detection using convolutional neural network. Tesi di Laurea in Cybercrime and fraud detection, Luiss Guido Carli, relatore Gianluigi Me, pp. 21. [Bachelor's Degree Thesis]
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Abstract/Index
Cyber trends. Defensive sustems. CNN approach. Related works. Malware identification based on statistical analysis. Malware identification based on dynamic analysis. Malware detection using CNN. Methods. Binary visualization into image. CNN architectures. Proposed work. Datased description. Model overview. Experiments and evaluation.
References
Bibliografia: pp. 20-21.
| Thesis Type: | Bachelor's Degree Thesis |
|---|---|
| Institution: | Luiss Guido Carli |
| Degree Program: | Bachelor's Degree Programs > Bachelor's Degree Program in Management and Computer Science, English language (L-18) |
| Chair: | Cybercrime and fraud detection |
| Thesis Supervisor: | Me, Gianluigi |
| Academic Year: | 2022/2023 |
| Session: | Autumn |
| Deposited by: | Alessandro Perfetti |
| Date Deposited: | 06 Mar 2024 10:42 |
| Last Modified: | 06 Mar 2024 10:42 |
| URI: | https://tesi.luiss.it/id/eprint/38087 |
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