@inproceedings{1a2902c4baf24aa193702d2ba1e15bc8,
title = "Deep Learning Based Malware Analysis",
abstract = "Today, hundreds of thousands of new malicious files are being made. The existing pattern-based antivirus solution has difficulties in coping with such a large number of new malicious files. To solve these problems, artificial intelligence based malicious file detection methods have been proposed. In this paper, we propose a malicious file analysis method based on deep learning.",
keywords = "Attention, Deep learning, Malware analysis",
author = "Sunoh Choi",
note = "Publisher Copyright: {\textcopyright} 2021, Springer Nature Singapore Pte Ltd.; 11th International Conference on Computer Science and its Applications, CSA 2019 and 14th KIPS International Conference on Ubiquitous Information Technologies and Applications, CUTE 2019 ; Conference date: 18-12-2019 Through 20-12-2019",
year = "2021",
doi = "10.1007/978-981-15-9343-7\_54",
language = "English",
isbn = "9789811593420",
series = "Lecture Notes in Electrical Engineering",
publisher = "Springer Science and Business Media Deutschland GmbH",
pages = "395--400",
editor = "Park, \{James J.\} and Fong, \{Simon James\} and Yi Pan and Yunsick Sung",
booktitle = "Advances in Computer Science and Ubiquitous Computing - CSA-CUTE 2019",
}