Empirical assessment of machine learning-based malware detectors for Android - Measuring the gap between in-the-lab and in-the-wild validation scenarios.
Kevin AllixTegawendé F. BissyandéQuentin JéromeJacques KleinRadu StateYves Le TraonPublished in: Empir. Softw. Eng. (2016)
Keyphrases
- machine learning
- malware detection
- decision trees
- detect malicious
- machine learning methods
- mobile devices
- knowledge acquisition
- data mining
- learning systems
- object detection
- computational intelligence
- negative selection algorithm
- statistical learning theory
- explanation based learning
- knowledge discovery
- real world
- artificial intelligence
- natural language
- computer science
- information extraction
- inductive learning
- malicious code
- supervised learning
- computer vision
- natural language processing
- machine learning approaches
- learning tasks
- data sets
- active learning
- machine learning algorithms
- inductive logic programming
- text classification
- reverse engineering
- statistical methods
- learning algorithm
- knowledge representation