ANDROID MALWARE ANALYSIS USING ARTIFICIAL INTELLIGENCE - Ali Ahmed; Noman Khokhar; Nelson Alfonso; Karan Kumar (Spectrum of Engineering Sciences, 2025)
Mobile phones have become a crucial part of society and serve as more than just communication devices. The growing use of smartphones has led to a large number of apps, making it difficult for app marketplaces to validate their legitimacy. Conventional security solutions for computer malware are challenging to apply on mobile devices due to different resource management mechanisms. Implementing intelligent tools using the Machine Learning in the threat identification process of security software can improve its efficiency by analyzing data and identifying potential threats. This reduces the need for human intervention and allows for faster detection of risks, saving time and resources. Intelligent tools can also continuously monitor data and identify potential threats in real-time, further improving the threat identification process. In conclusion, the use of intelligent tools can significantly enhance the effectiveness of conventional security software and protect against potential threats. This can help prevent hacking and data theft and keep personal information safe and secure. Additionally, these intelligent tools can be easily integrated into current security systems, making it easy for organizations to improve their overall security posture.