ANALISIS PERBANDINGAN DETECTION TRAFFIC ANOMALY SERANGAN DDoS IPv4 DENGAN METODE NAÏVE BAYES DAN SUPPORT VECTOR MACHINE (SVM)

MAULANA, MUHAMAD CHENDY and Heryanto, Ahmad (2023) ANALISIS PERBANDINGAN DETECTION TRAFFIC ANOMALY SERANGAN DDoS IPv4 DENGAN METODE NAÏVE BAYES DAN SUPPORT VECTOR MACHINE (SVM). Undergraduate thesis, Sriwijaya University.

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Abstract

Anomaly traffic is a condition that results in an abnormality in network traffic. Anomaly detections is a monitoring to monitor the movement that occurs in the network system. DDoS attack or Distributed Denial of Service is a cyber attack by continuously sending fake traffic to a system or server. As a result, the server cannot manage all traffic, causing it to go down. In this research, traffic anomaly detection will be carried out using the naïve Bayes method and support vector machine to see a comparison of the two methods used in the detection of IPv4 ddos attacks. The results show that using the Naïve Bayes algorithm method produces an accuracy value of 99.68%, 99.68% precision, 99.68% recall, and 99.68% F1 score which is proven to be better than the Support Vector Machine method which produces an accuracy value of 85 .79%, 83.79% precision, 88.83% recall, and 86.24% F1 score in detecting traffic anomalies against DDoS attack data packets and normal data.

Item Type:	Thesis (Undergraduate)
Uncontrolled Keywords:	Sistem Komputer, Jaringan
Subjects:	T Technology > TA Engineering (General). Civil engineering (General) > TA1-2040 Engineering (General). Civil engineering (General) > TA158.7 Computer network resources Including the Internet
Divisions:	09-Faculty of Computer Science > 56201-Computer Systems (S1)
Depositing User:	Users 29009 not found.
Date Deposited:	03 Apr 2023 02:20
Last Modified:	03 Apr 2023 02:20
URI:	http://repository.unsri.ac.id/id/eprint/92422

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