2 citations · 2 across the 3 of their papers we have counts for
3 papers
Light up that Droid! On the Effectiveness of Static Analysis Features against App Obfuscation for Android Malware Detection
Borja Molina-Coronado, Antonio Ruggia, Usue Mori +3
Malware authors have seen obfuscation as the mean to bypass malware detectors based on static analysis features. For Android, several studies have confirmed that many anti-malware…
Efficient Concept Drift Handling for Batch Android Malware Detection Models
Molina-Coronado B., Mori U., Mendiburu A. +1
The rapidly evolving nature of Android apps poses a significant challenge to static batch machine learning algorithms employed in malware detection systems, as they quickly become…
Neuroevolutionary algorithms driven by neuron coverage metrics for semi-supervised classification
Roberto Santana, Ivan Hidalgo-Cenalmor, Unai Garciarena +2
In some machine learning applications the availability of labeled instances for supervised classification is limited while unlabeled instances are abundant. Semi-supervised learnin…