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

AZANDI, REZA MAHESA and Heryanto, Ahmad (2023) PENERAPAN ALGORITMA SUPPORT VECTOR MACHINE PADA PLATFORM QUANTUM COMPUTING DALAM PENDETEKSIAN MALICIOUS SOFTWARE. Undergraduate thesis, Sriwijaya University.

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Abstract

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%.

Item Type:	Thesis (Undergraduate)
Uncontrolled Keywords:	Pendeteksian Malware, Quantum Computing, Stochastic Gradient Descent, Support Vector Machine (SVM)
Subjects:	Q Science > Q Science (General) > Q334-342 Computer science. Artificial intelligence. Algorithms. Robotics. Automation.
Divisions:	09-Faculty of Computer Science > 56201-Computer Systems (S1)
Depositing User:	Reza Mahesa Azandi
Date Deposited:	17 Oct 2023 08:08
Last Modified:	17 Oct 2023 08:08
URI:	http://repository.unsri.ac.id/id/eprint/129891

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