Alam, ShahidYildirim, SerdarHassan, MahamatSogukpinar, Ibrahim2025-01-062025-01-062018978-1-5386-4184-2https://hdl.handle.net/20.500.14669/18262nd International Symposium on Multidisciplinary Studies and Innovative Technologies (ISMSIT) -- OCT 19-21, 2018 -- Kizilcahamam, TURKEYAccording to the recent Symantec threat reports, Android continues to be the most targeted mobile platform, the number of new mobile malware attacks grew by 105% from 2015 to 2016, and the number of new discovered mobile malware variants grew by 54% from 2016 to 2017. A recent McAfee threat report confers that the number of malware families found in the Google play increased by 30% in 2017. There is a need to develop new techniques and methods to stop this inundation of mobile malware attacks. In this paper we propose a new technique named Droid-DomTree that mines dominance tree of API calls in an Android APK for detecting malware. We develop, a sequential model of the dominance tree of API calls and a weighing scheme for assigning weights to each node in the dominance tree for efficient feature selection. A detection rate of 94.3% was obtained with 4 classifiers.eninfo:eu-repo/semantics/closedAccessAndroid APKMalware Analysis and DetectionDominance TreeAPI CallsMachine LearningConference Object195192WOS:000467794200034N/A