Malware Detection using Attributed CFG Generated by Pre-trained Language Model with Graph Isomorphism Network-Reference-Cited by-同舟云学术

Malware Detection using Attributed CFG Generated by Pre-trained Language Model with Graph Isomorphism Network

Published:2022-06 Issue: Volume: Page:
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Container-title:2022 IEEE 46th Annual Computers, Software, and Applications Conference (COMPSAC)
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Author:

Gao Yun¹,Hasegawa Hirokazu²,Yamaguchi Yukiko³,Shimada Hajime¹

Affiliation:

1. Graduate School of Informatics, Nagoya University,Nagoya,Japan

2. National Institute of Informatics,Center for Strategic Cyber Resilience, Research and Development,Tokyo,Japan

3. Nagoya University,Information Technology Center,Nagoya,Japan

Funder

JST SPRING

Publisher

IEEE

Link

Reference24 articles.

2. Learning to Detect and Classify Malicious Executables in the Wild;kolter;J Mach Learn Res,2006

4. Malware Detection by Eating a Whole EXE;raff;AAAI Workshops 2018,2018

5. MWS Datasets for Anti-Malware Research - Contribution to the community and its challenges- (in Japanese);terada;IPSJ SIG Technical Report,2020

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