Adversarial attacks against Windows PE malware detection: A survey of the state-of-the-art

X Ling, L Wu, J Zhang, Z Qu, W Deng, X Chen… - Computers & …, 2023 - Elsevier
Malware has been one of the most damaging threats to computers that span across multiple
operating systems and various file formats. To defend against ever-increasing and ever …

Adversarial machine learning: A multilayer review of the state-of-the-art and challenges for wireless and mobile systems

J Liu, M Nogueira, J Fernandes… - … Surveys & Tutorials, 2021 - ieeexplore.ieee.org
Machine Learning (ML) models are susceptible to adversarial samples that appear as
normal samples but have some imperceptible noise added to them with the intention of …

[HTML][HTML] Malware threat affecting financial organization analysis using machine learning approach

R Rawat, SK Sarangi, YN Rimal, P William… - International Journal of …, 2022 - igi-global.com
Since 2014, Emotet has been using Man-in-the-Browsers (MITB) attacks to target companies
in the finance industry and their clients. Its key aim is to steal victims' online money-lending …

Functionality-preserving black-box optimization of adversarial windows malware

L Demetrio, B Biggio, G Lagorio, F Roli… - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
Windows malware detectors based on machine learning are vulnerable to adversarial
examples, even if the attacker is only given black-box query access to the model. The main …

Mab-malware: A reinforcement learning framework for blackbox generation of adversarial malware

W Song, X Li, S Afroz, D Garg, D Kuznetsov… - … of the 2022 ACM on Asia …, 2022 - dl.acm.org
Modern commercial antivirus systems increasingly rely on machine learning (ML) to keep up
with the rampant inflation of new malware. However, it is well-known that machine learning …

Obfuscation-resilient android malware analysis based on complementary features

C Gao, M Cai, S Yin, G Huang, H Li… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
Existing Android malware detection methods are usually hard to simultaneously resist
various obfuscation techniques. Therefore, bytecode-based code obfuscation becomes an …

A Survey of strategy-driven evasion methods for PE malware: transformation, concealment, and attack

J Geng, J Wang, Z Fang, Y Zhou, D Wu, W Ge - Computers & Security, 2024 - Elsevier
The continuous proliferation of malware poses a formidable threat to the cyberspace
landscape. Researchers have proffered a multitude of sophisticated defense mechanisms …

[HTML][HTML] Evadedroid: A practical evasion attack on machine learning for black-box android malware detection

H Bostani, V Moonsamy - Computers & Security, 2024 - Elsevier
Over the last decade, researchers have extensively explored the vulnerabilities of Android
malware detectors to adversarial examples through the development of evasion attacks; …

Challenges and pitfalls in malware research

M Botacin, F Ceschin, R Sun, D Oliveira, A Grégio - Computers & Security, 2021 - Elsevier
As the malware research field became more established over the last two decades, new
research questions arose, such as how to make malware research reproducible, how to …

Antiviruses under the microscope: A hands-on perspective

M Botacin, FD Domingues, F Ceschin, R Machnicki… - Computers & …, 2022 - Elsevier
AntiViruses (AVs) are the main defense line against attacks for most users and much
research has been done about them, especially proposing new detection procedures that …