A Deep Reinforcement Learning Framework to Evade Black-Box Machine Learning Based IoT Malware Detectors Using GAN-Generated Influential Features

In the internet of things (IoT) networks, machine learning (ML) is significantly used for malware and adversary detection. Recently, research has shown that adversarial attacks have put ML-based models at risk. This problem is exacerbated in an IoT environment because of the absence of adequate secu...

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Hlavní autoři:	Rahat Maqsood Arif, Muhammad Aslam, Shaha Al-Otaibi, Ana Maria Martinez-Enriquez, Tanzila Saba, Saeed Ali Bahaj, Amjad Rehman
Médium:	Artigo
Jazyk:	Inglês
Vydáno:	IEEE 2023-01-01
Edice:	IEEE Access
Témata:	Generative adversarial network portable executable PE malware adversarial attack malware evasion deep reinforcement learning technological development
On-line přístup:	https://ieeexplore.ieee.org/document/10322868/
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