Skripsi

DETEKSI ANCAMAN URL BERBAHAYA BERBASIS EMBEDDING FEATURE EXTRACTION MENGGUNAKAN METODE ARTIFICIAL NEURAL NETWORK

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Penilaian

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Malicious URLs are often used in cyber attacks, especially in an attempt to steal sensitive information, spread malware or commit online fraud. Cybercriminals will usually spread these attacks through fake advertisements, email spam and various other ways to attract victims' attention. There are various ways to prevent these attacks from continuing to occur. This research proposes an innovative approach by integrating subword embedding technique for feature extraction. SMOTE is used to overcome the imbalance between classes. An artificial neural network (ANN) classification model is proposed considering its superiority in capturing more complex information.

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Availability

Inventory Code	Barcode	Call Number	Location	Status
2507005490	T183172	T1831722025	Central Library (Referensi)	Available but not for loan - Not for Loan

Detail Information

Series Title

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Call Number

T1831722025

Publisher

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

Collation

xvi, 125 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

SEPTA

Other version/related

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