ACMFNN: A Novel Design of an Augmented Convolutional Model for Intelligent Cross-Domain Malware Localization via Forensic Neural Networks
The detection and localization of malwares using spatial and temporal data patterns require the development of efficient deep learning models. These models employ various techniques such as feature extraction, feature selection, data classification, and post-processing to achieve their objectives. W...
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| Huvudupphov: | , , |
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| Materialtyp: | Artigo |
| Språk: | Inglês |
| Utgiven: |
IEEE
2023-01-01
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| Serie: | IEEE Access |
| Ämnen: | |
| Länkar: | https://ieeexplore.ieee.org/document/10216992/ |
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