Social Impact on Android Applications using Decision Tree

Waseem Iqbal, Muhammad Arfan, Muhammad Asif

Abstract


Mobile phones have evolved very rapidly from black and white to smart phones. Google has launched Android operating system (OS), based on Linux targeting the smart phones. After this, people became addicted to these smart phones due to the facilities provided by these phones. But the security leaks possess in Android are the big hurdle to use it in a secured way. The Android operating system is mostly used because it is an Open Source/freeware and most of its applications are also freely available on different online applications stores. To install  any application,  we  must accept  the  terms  and conditions  regarding  the access  to multiple part of device and personal information, otherwise unable to install these free or paid applications.  The main problem is that when we allow the access to multiple parts of our device and our personal information, the inherited security leaks become more vulnerable to threat.  A very simple and handy solution is that we only install the applications that are positively reviewed by other users who already installed and are still using these applications. We implement the Decision Tree, a machine learning technique, to analyze these positively reviewed application and make a recommendation  whether to install them in the device or not.


Keywords


Android; Decision tree; Machine Learning Technique; Social Impact; Entropy

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References


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