DETEKSI SERANGAN DISTRIBUTED DENIAL OF SERVICE (DDOS) PADA PERANGKAT SMARTHOME MENGGUNAKAN METODE LONG SHORT - TERM MEMORY (LSTM)

MAKIYAH, MAKIYAH and Stiawan, Deris and Afifah, Nurul (2025) DETEKSI SERANGAN DISTRIBUTED DENIAL OF SERVICE (DDOS) PADA PERANGKAT SMARTHOME MENGGUNAKAN METODE LONG SHORT - TERM MEMORY (LSTM). Undergraduate thesis, Sriwijaya University.

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Abstract

The Internet of Things (IoT) has brought convenience to everyday life, particularly through the implementation of smarthome devices. However, the connectivity of these devices also increases their vulnerability to cyber threats, especially Distributed Denial of Service (DDoS) attacks, which can severely disrupt system operations. This study aims to detect DDoS attacks on smarthome devices using the Long Short-Term Memory (LSTM) method, known for its effectiveness in handling sequential data. The dataset used is derived from COMNETS Smarthome, initially in .pcap format and later extracted to .csv using CICFlowMeter. The training process includes several stages: data cleaning, feature selection, label encoding,normalization, and data splitting (training, validation, testing). Evaluation results show that the LSTM model can detect DDoS attacks with a peak accuracy of 99.73%, precision of 99.54%, recall of 100%, and F1-score of 99.77% using an 80:10:10 data split ratio. Therefore, the LSTM model is proven to be effective for DDoS attack detection on smarthome devices and has strong potential to be implemented as an early warning system in IoT networks.

Item Type:	Thesis (Undergraduate)
Uncontrolled Keywords:	Internet of Things, Smarthome, DDoS, SNORT, LSTM, Deep Learning, Attack Detection
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:	Makiyah Makiyah
Date Deposited:	30 Jun 2025 02:04
Last Modified:	30 Jun 2025 02:04
URI:	http://repository.unsri.ac.id/id/eprint/176056

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