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LSTM Model for Malware Detection by gouliroufai3 is a document available to read on EtoBox.

What is LSTM Model for Malware Detection about?

The document presents a model based on LSTM neural networks for identifying five different types of malware, addressing the challenges in malware classification due to the lack of publicly available datasets. A new large dataset was introduced for this purpose, and the proposed model achieved an accuracy of 67.60% on unseen programs. The paper discusses the types of malware included, the methodologies for malware analysis, and the architecture of the LSTM model used for classification.

Author

gouliroufai3

Language

EN