The study seeks to tackle the growing prevalence of mobile phones via the use of modern techniques such as artificial intelligence and machine learning. Mobile devices are crucial for everyday activities and confidential information, becoming them important targets for cybercriminals. The research investigates sophisticated detection methods using artificial intelligence and machine learning to recognize attacks by algorithms that train on extensive datasets of established attack patterns. Behavioral monitoring is examined to evaluate interactions with the mobile system and identify possible hazards. Deep learning systems analyze extensive data sets to identify intricate patterns, facilitating expedited and precise identification of emerging risks. The study highlights the significance of user knowledge in reducing hazards linked to human irresponsibility, including susceptibility to phishing attacks and the installation of harmful software. The research advocates for cooperation among stakeholders to develop holistic solutions for improving the safety of mobile devices.