This paper enhances Android app security by detecting cyber threats such as malware and phishing using machine learning. By analyzing app behavior, permissions, and metadata, machine learning algorithms classify apps as safe or malicious. This system ensures safer mobile app usage and helps in curbing cybercrimes on Android platforms. The proliferation of Android devices has transformed mobile technology, making smartphones indispensable in daily life. However, this widespread adoption has attracted cybercriminals, leading to a surge in malicious applications (malware) targeting the Android ecosystem. Malware poses significant threats, including unauthorized data access, financial theft, and privacy breaches. Traditional signature-based detection methods are increasingly inadequate against sophisticated and evolving malware, necessitating more advanced detection techniques.
