Analysis and Detection of Malware in Android Applications Using Machine Learning
作者： Umme Sumaya Jannat , Syed Md. Hasnayeen , Mirza Kamrul Bashar Shuhan , Md. Sadek Ferdous
DOI: 10.1109/ECACE.2019.8679493
关键词: Machine learning 、 Android (operating system) 、 Mobile phone 、 Feature extraction 、 Static analysis 、 Computer science 、 Artificial intelligence 、 Malware
摘要: The Android Operating System, being the leading OS for mobile phone devices, is also primary target malicious attackers. Applications installed in present a way attackers to breach security of system. Therefore, it essential study and analyze applications so that can be properly identified. Static dynamic analyses are two major methods by which analyzed segregate from benign ones. This paper presents several leveraging machine learning models. Taking different features applying various classifiers, we show analysis model hit up 93% accuracy detecting malware whereas static achieve 81% accuracy. Moreover, trending Bangladeshi as part this resulting into acquisition interesting insights.
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