Black Box Attacks using Adversarial Samples against Machine Learning Malware Classification to Improve Detection.
Raphael Labaca CastroGabi Dreo RodosekPublished in: AIMS (2018)
Keyphrases
- black box
- machine learning
- rule extraction
- machine learning methods
- training samples
- black boxes
- pattern recognition
- decision trees
- detect malicious
- supervised learning
- support vector machine
- supervised machine learning
- feature selection
- machine learning algorithms
- text classification
- attack detection
- false positives
- support vector
- model selection
- training set
- feature extraction
- classification accuracy
- test cases
- hybrid systems
- integration testing
- white box testing
- case study
- reverse engineering
- watermarking scheme
- neural network
- anomaly detection
- malware detection
- computational intelligence
- malicious code
- feature vectors