Skripsi

PENERAPAN ALGORITMA SUPPORT VECTOR MACHINE PADA PLATFORM QUANTUM COMPUTING DALAM PENDETEKSIAN MALICIOUS SOFTWARE.

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Penilaian

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The necessity for more efficient computing will increase as technology develops, with quantum computing able to provide more efficient computing power than conventional computing. Technological developments will also influence the number of cyber attacks, the most common cyber attacks currently encountered are malware attacks. One of the algorithm that is suitable for classification is the Support Vector Machine. The use of Support Vector Machine with quantum computing is assisted by the Stochastic Gradient Descent method to optimize parameters. In this research, quantum circuit resource optimization and scenario testing were carried out to obtain optimal models and results. The quantum circuit resources that will be optimized are the quantum logic gate circuit and the number of qubits used. There are a total of nine scenarios that will be tested, consisting of dividing the ratio of train data to test data and variations in the learning rate parameter values. The dataset used is CIC-MalMem-2022 which has two labels, namely malware and benign. The best model performance from this research produced precision values of 97.42%, recall 98.69%, specificity 96.98%, f1-score 98.05%, and accuracy 97.9%.

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Availability

Inventory Code	Barcode	Call Number	Location	Status
2307006242	T129891	T1298912023	Central Library (Referens)	Available

Detail Information

Series Title

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Call Number

T1298912023

Publisher

Indralaya : Prodi Sistem Komputer, Fakultas Ilmu Komputer Universitas Sriwijaya., 2023

Collation

xiv, 70 hlm.; ilus.; 29 cm

Language

Indonesia

ISBN/ISSN

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Classification

003.307

Content Type

Text

Media Type

unmediated

Carrier Type

-

Edition

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Subject(s)

Model dan simulasi komputer
Prodi Sistem Komputer

Specific Detail Info

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Statement of Responsibility

MURZ

Other version/related

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