Automatic Feature Extraction, Categorization and Detection of Malicious Code in Android Applications

Muhammad Zuhair Qadir, Atif Nisar Jilani, Hassam Ullah Sheikh


Since Android has become a popular software platform for mobile devices recently; they offer almost the same functionality as personal computers. Malwares have also become a big concern. As the number of new Android applications tends to be rapidly increased in the near future, there is a need for automatic malware detection quickly and efficiently. In this paper, we define a simple static analysis approach to first extract the features of the android application based on intents and categories the application into a known major category and later on mapping it with the permissions requested by the application and also comparing it with the most obvious intents of category. As a result, getting to know which apps are using features which they are not supposed to use or they do not need.

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This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.