Skripsi

DETEKSI ANCAMAN SSL PINNING BYPASS DAN DDOS MENGGUNAKAN NAIVE BAYES PADA KEAMANAN SMARTHOME

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The development of smart home technology provides convenience for users in managing household devices automatically and through internet connectivity; however, it also raises potential security threats, such as SSL Pinning Bypass, which allows attackers to intercept communications, and Distributed Denial of Service (DDoS) attacks, which can disrupt service availability. To address these issues, this study employs the Naive Bayes algorithm as a classification method to detect attack patterns in smart home network traffic. The dataset used consists of normal traffic, traffic indicated as SSL Pinning Bypass, and DDoS attack traffic, which are then processed through preprocessing, feature extraction, training, and model testing stages. The experimental results demonstrate that the Naive Bayes algorithm is capable of classifying traffic with high accuracy and produces favorable precision, recall, and f1-score values in distinguishing between normal and malicious traffic. Therefore, the application of the Naive Bayes algorithm is proven to be effective in detecting SSL Pinning Bypass and DDoS threats in smart home systems and is expected to serve as a foundation for the development of more adaptive machine learning- based security systems in the future.

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Detail Information

Series Title

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Call Number

T1903172025

Publisher

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

Collation

xv, 101 hlm.; ilus.; tab.; 29 cm.

Language

Indonesia

ISBN/ISSN

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Classification

005.820 7

Content Type

Text

Media Type

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Carrier Type

-

Edition

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Subject(s)

Prodi Sistem Komputer
Keamanan Jaringan--Naive Bayes

Specific Detail Info

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Statement of Responsibility

MI

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