A public Android malware
app dataset and popular benign apps collected from the
Android Market are used for evaluating the effectiveness of the
proposed approach in terms of its grouping ability and
effectiveness in identifying Android malware. The proposed
approach successfully identifies malicious Android Apps with
nearly 100% accuracy, precision, and recall rate.