Noisy Label Detection for Multi-labeled Malware.
Naoki FukushiToshiki ShibaharaHiroki NakanoTakashi KoideDaiki ChibaPublished in: CCNC (2024)
Keyphrases
- detection algorithm
- noisy environments
- detection rate
- anomaly detection
- malware detection
- false alarms
- automatic detection
- detection accuracy
- labeling process
- object detection
- detection method
- false positives
- class labels
- supervised learning
- pairwise
- reverse engineering
- training data
- low signal to noise ratio
- detect malicious
- noisy data
- manual labeling
- label noise
- malicious executables
- manually labeled
- noise free
- data sets
- training set
- feature space
- computer vision
- neural network