Is Feature Selection Secure against Training Data Poisoning?
Huang XiaoBattista BiggioGavin BrownGiorgio FumeraClaudia EckertFabio RoliPublished in: ICML (2015)
Keyphrases
- training data
- feature selection
- classification accuracy
- classification models
- text categorization
- naive bayes
- test data
- feature space
- training set
- support vector machine
- feature set
- decision trees
- learning algorithm
- data sets
- mutual information
- training process
- key management
- feature extraction
- machine learning
- supervised learning
- labeled data
- security issues
- text classification
- dimensionality reduction
- training samples
- training instances
- test set
- prior knowledge
- security requirements
- redundant features
- cryptographic protocols
- irrelevant features
- support vector
- security analysis
- feature weighting
- training examples
- model selection
- training dataset
- feature selection algorithms
- semi supervised learning
- feature subset
- lightweight
- method for feature selection
- sensitive data
- learned from training data
- unsupervised learning
- class labels