Certified Robustness of Static Deep Learning-based Malware Detectors against Patch and Append Attacks.
Daniel GibertGiulio ZizzoQuan LePublished in: AISec@CCS (2023)
Keyphrases
- deep learning
- detect malicious
- dynamic analysis
- malicious code
- unsupervised learning
- unsupervised feature learning
- machine learning
- mental models
- static analysis
- detecting malicious
- attack scenarios
- deep architectures
- object detection
- weakly supervised
- image patches
- anti virus
- malware detection
- domain specific
- input image
- high dimensional
- decision trees