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Matthew Gaber: Peekaboo Transformer Models
- Source :
- Research Datasets
- Publication Year :
- 2024
-
Abstract
- Finding automated AI techniques to proactively defend against malware has become increasingly critical. The ability of an AI model to correctly classify novel malware is dependent on the quality of the features it is trained with. In turn, the authenticity and quality of the features is dependent on the analysis tool and the dataset. Peekaboo, a Dynamic Binary Instrumentation tool defeats evasive malware to capture its genuine behavior. Transformer models trained with Peekaboo data excel in detecting new malicious functions, outperforming prior approaches in novel ransomware detection.This dataset contains the fine tuned models and the Colab scripts used for training and testing.
Details
- Database :
- OAIster
- Journal :
- Research Datasets
- Notes :
- Research Datasets
- Publication Type :
- Electronic Resource
- Accession number :
- edsoai.on1452785895
- Document Type :
- Electronic Resource