Skripsi

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

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Penilaian

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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.

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Availability

Inventory Code	Barcode	Call Number	Location	Status
2507003561	T176056	T1760562025	Central Library (Reference)	Available but not for loan - Not for Loan

Detail Information

Series Title

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Call Number

T1760562025

Publisher

Indralaya : Prodi Sistem Komputer, Fakultas Ilmu Komputer Universitas Sriwijaya., 2025

Collation

xvi, 90 hlm.; ilus.; tab.; 29 cm.

Language

Indonesia

ISBN/ISSN

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Classification

004.07

Content Type

Text

Media Type

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Carrier Type

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Edition

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Subject(s)

Sistem komputer

Specific Detail Info

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Statement of Responsibility

MI

Other version/related

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