Skripsi

SISTEM DETEKSI MULTI-CLASSIFICATION SERANGAN CYBER MENGGUNAKAN METODE DEEP LEARNING CNN.

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Penilaian

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Cyber attacks have become an increasing threat to the security of modern information systems. To overcome the complexity and diversity of attacks that occur, a sophisticated and reliable detection approach is needed. In this research, we propose a multi-classification cyber attack detection system that adopts the Deep Learning Convolutional Neural Network (CNN) method. CNNs have proven effective in solving image classification problems and have shown great potential in cyber attack detection applications. We collect a representative dataset of various types of cyber attacks and train a CNN model to identify attacks in multi-classification categories. Experiments were carried out to evaluate the performance of the proposed detection system, including testing the detection speed and accuracy level. The results show that the proposed system is capable of detecting cyber attacks with a high degree of accuracy, while also maintaining sufficient detection speed. The main contribution of this research is the development of a detection system that can provide effective protection against various cyber attacks, by exploiting the power of the Deep Learning CNN method.

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Availability

Inventory Code	Barcode	Call Number	Location	Status
2407002488	T143129	T1431292024	Central Library (REFERENCES)	Available but not for loan - Not for Loan

Detail Information

Series Title

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Call Number

T1431292024

Publisher

Indralaya : Prodi Sistem Komputer, Fakultas Ilmu Komputer., 2024

Collation

xvi, 187 hlm.; tab.; ilus.; 29 cm.

Language

Indonesia

ISBN/ISSN

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Classification

005. 109 207

Content Type

Text

Media Type

unmediated

Carrier Type

unspecified

Edition

-

Subject(s)

Prodi Sistem Komputer
Peretas

Specific Detail Info

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Statement of Responsibility

UIN Farrah

Other version/related

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