KLASIFIKASI SERANGAN BRUTE FORCE MENGGUNAKAN METODE CONVOLUTIONAL NEURAL NETWORK (CNN)

PUTRI, BELLA and Stiawan, Deris and Ubaya, Huda (2021) KLASIFIKASI SERANGAN BRUTE FORCE MENGGUNAKAN METODE CONVOLUTIONAL NEURAL NETWORK (CNN). Undergraduate thesis, Sriwijaya University.

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Abstract

Brute Force is a password cracking attack against a computer security system. In launching the attack, the perpetrator uses a trial-and-error method by trying all password combinations in order to pass the authentication process. Actually, brute force is an old and simple attack method, but this type of cybercrime has a fairly high success rate and is considered very effective. That is why this attack is still popular today and is widely used by hackers to carry out their criminal acts. The method used in this research is Convolutional Neural Network (CNN). In this study, classification was carried out for 3 classes of network attacks with a composition of 50% to 80% of training data, on the parameters of learning rate, batch size, and relu activation. Based on the test results, CNN model 1 produces the best performance in classifying with 99.99% accuracy, 100% precision, 100% specificity, and 99.99% fi-score.

Item Type:	Thesis (Undergraduate)
Uncontrolled Keywords:	Klarifikasi, Brute Force, Convolutional Neural Netwrok (CNN)
Subjects:	T Technology > T Technology (General) > T1-995 Technology (General)
Divisions:	09-Faculty of Computer Science > 56201-Computer Systems (S1)
Depositing User:	Bella Putri
Date Deposited:	25 Jan 2022 02:36
Last Modified:	25 Jan 2022 02:36
URI:	http://repository.unsri.ac.id/id/eprint/62424

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