GA-StackingMD: Android Malware Detection Method Based on Genetic Algorithm Optimized Stacking

With the rapid development of network and mobile communication, intelligent terminals such as smartphones tablet computers have changed people’s daily life work. However, malware viruses, Trojans, extortion applications introduced threats to personal privacy social security. Malware Android operating system has a great variety updates rapidly. detection is faced with problems high feature dimension unsatisfied accuracy single classification algorithms. In this work, an framework GA-StackingMD presented, which employs Stacking compose five different base classifiers, Genetic Algorithm applied optimize hyperparameters framework. Experiments show that could effectively improve compared classifiers. The presented achieves 98.43% 98.66% accuracies on CIC-AndMal2017 CICMalDroid2020 data sets, shows effectiveness feasibility proposed method.