Permission-Based Android Malware Identification

Modern society has made mobile devices a necessary component in the daily lives of humans, and malware is growing at the same time. Users often utilize Android programs to conduct a variety of tasks, and the security of these applications depends on the rights that users provide to them. Malware attackers now frequently target the Android platform. Before installing an application, it is crucial to utilize a method to identify Android malware. Then, models were created using various machine-learning approaches by examining the current malware activity patterns and applying the information to identify any similar behavior carried out by unidentified attackers. So, a system that can recognize permission requests that are often asked or not asked by comparable applications might be used to reduce the chance of becoming a victim of the malware. There is no existing method for a person to verify that any application he installs for usage isn't malware. Instead, he must trust the application vendor. This gives us the opportunity to suggest and create a system that may really alert the user if any discrepancies are discovered in the permission list that is obtained from them.