Adversarial Malware Binaries: Evading Deep Learning for Malware Detection in Executables-Reference-Cited by-同舟云学术

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Adversarial Malware Binaries: Evading Deep Learning for Malware Detection in Executables

Published:2018-09 Issue: Volume: Page:
ISSN:
Container-title:2018 26th European Signal Processing Conference (EUSIPCO)
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Author:

Kolosnjaji Bojan,Demontis Ambra,Biggio Battista,Maiorca Davide,Giacinto Giorgio,Eckert Claudia,Roli Fabio

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/8537458/8552938/08553214.pdf?arnumber=8553214

Cited by 215 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

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2. Explainability Guided Adversarial Evasion Attacks on Malware Detectors;2024 33rd International Conference on Computer Communications and Networks (ICCCN);2024-07-29

3. LateBA: Latent Backdoor Attack on Deep Bug Search via Infrequent Execution Codes;Proceedings of the 15th Asia-Pacific Symposium on Internetware;2024-07-24

4. Defend against adversarial attacks in malware detection through attack space management;Computers & Security;2024-06

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