2 papers
cs.CR2024
Evading Deep Learning-Based Malware Detectors via Obfuscation: A Deep Reinforcement Learning Approach
Brian Etter, James Lee Hu, Mohammedreza Ebrahimi +3
Adversarial Malware Generation (AMG), the generation of adversarial malware variants to strengthen Deep Learning (DL)-based malware detectors has emerged as a crucial tool in the d…
cs.CR2021
Single-Shot Black-Box Adversarial Attacks Against Malware Detectors: A Causal Language Model Approach
James Lee Hu, Mohammadreza Ebrahimi, Hsinchun Chen
Deep Learning (DL)-based malware detectors are increasingly adopted for early detection of malicious behavior in cybersecurity. However, their sensitivity to adversarial malware va…