Android Malware Prediction using Efficient Learning Approach for Cybersecurity

Abstract— Android malware is a term used to refer to malicious software that is designed to infect a certain kind of device, in this instance smartphones that run the Android operating system. Malware is able to thrive in an environment that is made feasible by Android's less secure platform. This platform includes the Play Store, from which users are able to download programmes, as well as the ability for Android users to side load content from the internet. Both of these features allow for the distribution of malware. This study presents the use of machine learning methods for the purpose of predicting malicious android software. Additionally, performance enhancements are given. The simulation is run using Python Sypder 3.7, which is the programme that is used to carry it out. The outcomes of the simulation indicate that there has been an improvement in the standard of the performance indicators. Keywords— Android, SVM, MLP, Malware, Artificial Intelligence, Secuiry, Attack, Cyber.