Mobile banking Trojan detection using Naive Bayes / Anis Athirah Masmuhallim

Mobile phones have become immensely popular as intelligent terminals worldwide. The open-source nature of mobile platforms has facilitated the development of third- party mobile applications, but it has also created an environment for mobile malware to thrive. Unfortunately, the abundance of mobile applications and lax management of some app stores has led to potential risks for mobile users, including privacy breaches and malicious deductions of fees, among other adverse consequences. This research presents a mobile malware static detection method based on Naive Bayes. The approach aims to offer a solution to protect users from potential threats such as Banking Trojan malware. The objectives of this project are to study the requirement of the Naive Bayes algorithm in Mobile Banking Trojan detection, to develop a webbased detection system for Mobile Banking Trojan using Naive Bayes, and to evaluate the performance and accuracy of the Naive Bayes algorithm in the Mobile Banking Trojan detection. The methodology of this project consists of the research framework, preliminary study, design, development, and performance evaluation.