DETEKSI SERANGAN DISTRIBUTED DENIAL OF SERVICE (DDOS) PADA SISTEM SMARTHOME MENGGUNAKAN METODE CONVOLUTIONAL NEURAL NETWORK (CNN)

TYAS, DIAH AYUNING and Stiawan, Deris and Afifah, Nurul (2025) DETEKSI SERANGAN DISTRIBUTED DENIAL OF SERVICE (DDOS) PADA SISTEM SMARTHOME MENGGUNAKAN METODE CONVOLUTIONAL NEURAL NETWORK (CNN). Undergraduate thesis, Sriwijaya University.

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Abstract

The Internet of Things (IoT) offers numerous benefits but also increases security risks, one of which is Distributed Denial of Service (DDoS) attacks. These attacks can cripple Smarthome systems by flooding the network with excessive data traffic. This research aims to detect DDoS attacks on Smarthome devices using the Convolutional Neural Network (CNN) method. The dataset used was obtained from COMNETS in PCAP file format, which was then extracted into CSV format using CICFlowMeter. The data was processed through several preprocessing stages, including label encoding, feature selection, normalization, reshaping, and data splitting. The CNN model was built using an architecture consisting of Conv1D, MaxPooling1D, Flatten, Dense, and Dropout layers. The model was evaluated using accuracy, precision, recall, and F1-score metrics. The best results were obtained with an accuracy of 98.28%, precision of 98.23%, recall of 100%, and F1-score of 98.28%. These results indicate that the CNN method is highly effective in detecting DDoS attacks on IoT-based Smarthome systems in real time and with high accuracy.

Item Type:	Thesis (Undergraduate)
Uncontrolled Keywords:	Internet of Things, Smarthome, DDoS, CNN, Deep Learning, Network Security
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:	Diah Ayuning Tyas
Date Deposited:	30 Jun 2025 01:34
Last Modified:	30 Jun 2025 01:34
URI:	http://repository.unsri.ac.id/id/eprint/170562

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