Yazar "Hassan, Mahamat" seçeneğine göre listele

Listeleniyor 1 - 2 / 2
  • [ X ]
    Öğe
    Mining Dominance Tree of API Calls for Detecting Android Malware
    (IEEE, 2018) Alam, Shahid; Yildirim, Serdar; Hassan, Mahamat; Sogukpinar, Ibrahim
    According 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.
  • [ X ]
    Öğe
    Mininng Dominance Tree of API Calls for Detecting Android Malware
    (Institute of Electrical and Electronics Engineers Inc., 2018) Alam, Shahid; Yildirim, Serdar; Hassan, Mahamat; Sogukpinar, Ibrahim
    According 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. © 2018 IEEE.