DETEKSI SERANGAN MALWARE ANDROID REVERSE TCP PADA SMALL BOARD COMPUTER DENGAN METODE NAÏVE BAYES

SAPUTRA, DHANI MEDIANTO and Stiawan, Deris and Hermansyah, Adi (2025) DETEKSI SERANGAN MALWARE ANDROID REVERSE TCP PADA SMALL BOARD COMPUTER DENGAN METODE NAÏVE BAYES. Undergraduate thesis, Sriwijaya University.

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Abstract

Android malware threats using reverse TCP techniques are increasing and require effective detection methods. This study develops a detection systemusing the Naïve Bayes algorithm implemented on a small board computer (Banana Pi). Network traffic datasets were created under three scenarios: normal, attack (reverse TCP), and combined. After labeling and preprocessing, the Naïve Bayes model was tested and achieved an accuracy of 97.56%, with 91.00% precision, 89.47% recall, and a 90.23% F1-score. The model’s performance was compared to two signature-based detection systems, Snort and Suricata, and showed more effective results, particularly in the combined scenario. These findings demonstrate that simple machine learning methods like Naïve Bayes can provide reliable malware detection, especially when applied on lightweight and low-cost devices such as SBCs.

Item Type:	Thesis (Undergraduate)
Uncontrolled Keywords:	Reverse TCP, Malware Android, Naïve Bayes, Banana Pi, IDS.
Subjects:	Q Science > Q Science (General) > Q334-342 Computer science. Artificial intelligence. Algorithms. Robotics. Automation. T Technology > T Technology (General) > T10.5-11.9 Communication of technical information > T10.68 Risk communication T Technology > T Technology (General) > T57.6-57.97 Operations research. Systems analysis > T57.85 Network systems theory Including network analysis Cf. TS157.5+ Scheduling
Divisions:	09-Faculty of Computer Science > 56201-Computer Systems (S1)
Depositing User:	Dhani Medianto Saputra
Date Deposited:	04 Sep 2025 03:36
Last Modified:	04 Sep 2025 03:36
URI:	http://repository.unsri.ac.id/id/eprint/183573

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