DETEKSI SERANGAN SSL PINNING BYPASS DAN DDOS PADA JARINGAN SMARTHOME MENGGUNAKAN METODE SUPPORT VECTOR MACHINE (SVM)

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DETEKSI SERANGAN SSL PINNING BYPASS DAN DDOS PADA JARINGAN SMARTHOME MENGGUNAKAN METODE SUPPORT VECTOR MACHINE (SVM)

Fiona Listia Utari - Personal Name;

The rapid development of the Internet of Things (IoT) has accelerated the implementation of smart home systems connected to the internet. However, this advancement also increases the risk of cyberattacks, particularly SSL Pinning Bypass, which threatens communication security, and Distributed Denial of Service (DDoS), which disrupts service availability. This study aims to detect both types of attacks in a smarthome network using the Support Vector Machine (SVM) method. The dataset used in this research is derived from the COMNETS Smarthome Dataset in pcap format and was extracted into CSV format using T-Shark. From 19 generated network traffic features, feature selection was performed using Recursive Feature Elimination with Cross-Validation (RFECV), resulting in 12 optimal features. The SVM model was then employed to classify network traffic into three classes: Normal traffic, SSL Pinning Bypass, and DDoS. The experimental results show that the SVM model achieved an overall accuracy of 99.78%. The obtained F1-scores were 86.77% for the Normal class, 98.98% for SSL Pinning Bypass, and 99.97% for DDoS. These findings indicate that the SVM method is highly effective in detecting SSL Pinning Bypass and DDoS attacks, and performs adequately in identifying normal traffic. Keywords: Smarthome, Internet of Things, SSL Pinning Bypass, DDoS, T-Shark, RFECV, Support Vector Machine.

Availability

Central Library (Reference) T1933952026

T193395

Available but not for loan - Not for Loan

Detail Information

Series Title: -
Call Number: T1933952026
Publisher: Indralaya : Prodi Sistem Komputer, Fakultas Ilmu Komputer Universitas Sriwijaya., 2026
Collation: xiii, 66 hlm.; ilus.; tab.; 29 cm
Language: Indonesia
ISBN/ISSN: -
Classification: 005.807
Content Type: Text
Media Type: unmediated
Carrier Type: -
Edition: -
Subject(s): Prodi Sistem Komputer
Support Vector Machine (SVM) – Pembelajaran Mesin
Specific Detail Info: -
Statement of Responsibility: KA

Other version/related

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KOMPARASI PADA KLASIFIKASI TRAFIK SERANGAN MALWARE BOTNET DENGAN METODE SUPPORT VECTOR MACHINE (SVM)		id
ANALISIS SENTIMEN REVIEW MOVIE PADA IMDB MENGGUNAKAN METODE SELEKSI FITUR INFORMATION GAIN DAN ALGORITMA SUPPORT VECTOR MACHINE (SVM).		id

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DETEKSI SERANGAN SSL PINNING BYPASS DAN DDOS PADA JARINGAN SMARTHOME MENGGUNAKAN METODE SUPPORT VECTOR MACHINE (SVM)

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