Malware detection performance of convolutional neural networks (CNN) and ByteEnc (our method).

<p>Malware detection performance of convolutional neural networks (CNN) and ByteEnc (our method).</p>

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Bibliographic Details
Main Author:	Eun-Jin Kim (305808) (author)
Other Authors:	Yun-Kyung Lee (10865965) (author), Sang-Min Lee (474684) (author), Jeong-Nyeo Kim (22421623) (author), Ah Reum Kang (8720862) (author), Mi-seo Kim (22421626) (author), Young-Seob Jeong (12800186) (author)
Published:	2025
Subjects:	Science Policy Biological Sciences not elsewhere classified Information Systems not elsewhere classified three file types network every day making neural network empirical results demonstrate capture local patterns natural language processing masked language modeling detect malicious activities based language models malware detection task malware detection services processes byte sequences p &# 8764 including conventional pre based language model trained transformer encoder malware detection language model byte sequences based model powerful encoder malicious attacks foundation model speech recognition sequence prediction sentence prediction recent studies possible combinations novel transformer news articles ms office image analysis fake prediction benchmark consisting approximately 2
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