Abstract: With the growth in the android market, there is a significant increase of apps with malicious activities. Ac- cording to ZDNet, 10-24% of apps over the Play store could be malicious applications. Over the layer, these apps look similar to any other standard app, but they impact the user system in harmful ways. The current methodologies to detect malwares are resource heavy as well as exhaustive, yet fail to compete with the pace of new malwares. So, We tried to approach this Problem using Machine Learning Techniques and developed a model to predict an Application for potential Malware risk.
Keywords: Android Permissions, Malware Detection, Random Forest, Machine Learning
| DOI: 10.17148/IARJSET.2021.81146