International Journal of Computer Science & Network Security

국제컴퓨터통신보호논문지학회 (International Journal of Computer Science & Network Security)
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Mitigating Mobile Malware Threats: Implementing Gaussian Naïve Bayes for Effective Banking Trojan Detection

  • 투고 : 2024.10.05
  • 발행 : 2024.10.30
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초록

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 Gaussian Naïve 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 Naïve Bayes algorithm in Mobile Banking Trojan detection, and to evaluate the performance and accuracy of the Gaussian Naïve Bayes algorithm in the Mobile Banking Trojan detection. This study presents a mobile banking trojan detection system utilizing the Gaussian Naïve Bayes algorithm, achieving a high classification accuracy of 95.83% in distinguishing between benign and trojan APK files.

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과제정보

We want to express our appreciation to the Universiti Teknologi Mara Cawangan Terengganu Kampus Kuala Terengganu for their constant support in getting the authors to publish this work.

참고문헌

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