DETEKSI SERANGAN DDOS DOS DAN MITM PADA JARINGAN SMARTHOME DENGAN MENGGUNAKAN METODE DECISION TREE

PRATAMA, EDO and Stiawan, Deris and Afifah, Nurul (2025) DETEKSI SERANGAN DDOS DOS DAN MITM PADA JARINGAN SMARTHOME DENGAN MENGGUNAKAN METODE DECISION TREE. Undergraduate thesis, Sriwijaya University.

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Abstract

Smart Home is a form of automation technology designed to facilitate household activities with the help of the Internet of Things (IoT). IoT technology enables objects around us, such as sensors, cameras, and smart devices, to connect to the Internet. However, the advancement of IoT technology also makes it a target for cyberattacks such as Distributed Denial of Service (DDoS), Denial of Service (DoS), and Man-in-the-Middle (MITM) attacks. In this study, the authors conducted a real-world simulation of attacks, including DDoS, DoS, and MITM, on vulnerable Smart Home devices as a form of security testing. The use of information security tools played a crucial role in the success of this testing, employing tools such as CapLoader, Network Miner, Dynamite Lab, and IDS Snort. Additionally, T-Shark was utilized to extract data from .pcap files into .csv format for testing with Machine Learning algorithms, specifically using the Decision Tree model. The results of the study demonstrated that the Decision Tree method with the Gini criterion achieved excellent performance, with the highest F1-scores recorded for the following categories: MITM at 98.68%, Benign at 99.97%, DDoS at 99.99%, and DoS at 99.96%.

Item Type:	Thesis (Undergraduate)
Uncontrolled Keywords:	Smarthome, DDoS, DoS, MiTM, Snort, T-Shark, Caploader, Network Miner, DynamiteLab, Decision Tree
Subjects:	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:	Edo Pratama
Date Deposited:	16 Jan 2025 14:45
Last Modified:	16 Jan 2025 14:45
URI:	http://repository.unsri.ac.id/id/eprint/165182

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