ByteShield: Adversarially Robust End-to-End Malware Detection through Byte Masking

Similar Items

• DeepTrust: Multi-Step Classification through Dissimilar Adversarial Representations for Robust Android Malware Detection
  by: Pulido-Cortázar, Daniel, et al.
  Published: (2025)
• Machine Learning for Windows Malware Detection and Classification: Methods, Challenges and Ongoing Research
  by: Gibert, Daniel
  Published: (2024)
• RoMA: Robust Malware Attribution via Byte-level Adversarial Training with Global Perturbations and Adversarial Consistency Regularization
  by: Sun, Yuxia, et al.
  Published: (2025)
• A Robust Defense against Adversarial Attacks on Deep Learning-based Malware Detectors via (De)Randomized Smoothing
  by: Gibert, Daniel, et al.
  Published: (2024)
• Certified Adversarial Robustness of Machine Learning-based Malware Detectors via (De)Randomized Smoothing
  by: Gibert, Daniel, et al.
  Published: (2024)