ML for Android Malware Detection

Clicks: 3
ID: 310521
2024
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Abstract
The past few years have witnessed the drastic increase of mobile apps providing various facilities for personal and business use. The proliferation of mobile apps is due to billions of users who enable developers to earn revenue through advertisements, in-app purchases, etc. Whenever users install a new app, they are under the risk of installing malware. Unlike desktop apps, mobile apps can have the privilege, after declared (e.g., in Manifest file of Android platform), to access sensitive information such as contact lists, SMS messages, GPS, etc. In this paper we proposed ML model for malware detection in the Android system. It predicts the malware from android data is to find the accuracy more reliable. In an Android Malware Detection using machine learning, ML algorithms can be employed to analyze and classify applications as either benign or malicious.
Reference Key
imported_1768936496_696fd4301b0af Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Pravin P Kalyankar
Journal International Journal of Science and Social Science Research
Year 2024
DOI
10.5281/zenodo.13346226
URL
https://www.ijsssr.com/j/article/view/283
Keywords Keywords not found

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