Functionality-Preserving Black-Box Optimization of Adversarial Windows Malware-Reference-Cited by-同舟云学术

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Functionality-Preserving Black-Box Optimization of Adversarial Windows Malware

Published:2021 Issue: Volume:16 Page:3469-3478
ISSN:1556-6013
Container-title:IEEE Transactions on Information Forensics and Security
language:
Short-container-title:IEEE Trans.Inform.Forensic Secur.

Author:

Demetrio Luca^ORCID,Biggio Battista^ORCID,Lagorio Giovanni,Roli Fabio,Armando Alessandro

Funder

Progetti di Rilevante Interesse Nazionale (PRIN) 2017 Project RexLearn through the Italian Ministry of Education, University and Research

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Computer Networks and Communications,Safety, Risk, Reliability and Quality

Link

http://xplorestaging.ieee.org/ielx7/10206/9151439/09437194.pdf?arnumber=9437194

Cited by 88 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

1. Adversarial Machine Learning in Industry: A Systematic Literature Review;Computers & Security;2024-10

2. Enhancing reinforcement learning based adversarial malware generation to evade static detection;Alexandria Engineering Journal;2024-07

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

4. Evaluating Realistic Adversarial Attacks against Machine Learning Models for Windows PE Malware Detection;Future Internet;2024-05-12

5. MalwareTotal: Multi-Faceted and Sequence-Aware Bypass Tactics against Static Malware Detection;Proceedings of the IEEE/ACM 46th International Conference on Software Engineering;2024-04-12

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