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Deep android malware detection
(ACM, 2017-03)
In this paper, we propose a novel android malware detection system that uses a deep convolutional neural network (CNN). Malware classification is performed based on static analysis of the raw opcode sequence from a ...
N-opcode Analysis for Android Malware Classification and Categorization
(IEEE, 2016-06)
Malware detection is a growing problem particularly on the Android mobile platform due to its increasing popularity and accessibility to numerous third party app markets. This has also been made worse by the increasingly ...
N-gram Opcode Analysis for Android Malware Detection
(2016-11)
Android malware has been on the rise in recent years due to the increasing popularity of Android and the proliferation of third party application markets. Emerging Android malware families are increasingly adopting ...
Dynalog: An Automated Dynamic Analysis Framework for Characterizing Android Applications
(IEEE, 2016-06)
Android is becoming ubiquitous and currently has the largest share of the mobile OS market with billions of application downloads from the official app market. It has also become the platform most targeted by mobile malware ...
EMULATOR vs REAL PHONE: Android Malware Detection Using Machine Learning
(ACM, 2017-03-24)
The Android operating system has become the most popular operating system for smartphones and tablets leading to a rapid rise in malware. Sophisticated Android malware employ detection avoidance techniques in order to hide ...