DETEKSI SERANGAN SMURF ATTACK MENGGUNAKAN ALGORITMA RANDOM FOREST

ARIEF, MUHAMMAD and Heryanto, Ahmad (2021) DETEKSI SERANGAN SMURF ATTACK MENGGUNAKAN ALGORITMA RANDOM FOREST. Undergraduate thesis, Sriwijaya Universiy.

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Abstract

This final project focuses on detecting smurf attacks to be categorized as normal data or attacks. The smurf attack data packet is an ICMP packet, so in this study the focus is on the ICMP protocol. In making the dataset taken on the local network and divided into two datasets, namely normal datasets, and attack datasets. In performing detection, using ICMP message format in order to recognize attributes that are considered as attack patterns from smurf attacks such as frame length, icmp type, icmp identifier. So that attribute is used as a parameter in the classification with the random forest algorithm. The system that has been built with the random forest algorithm produces an accuracy rate of 99.99% of training data and 99.99% of testing data.

Item Type:	Thesis (Undergraduate)
Uncontrolled Keywords:	Smurf Attack, Random Forest, Accuracy
Subjects:	T Technology > T Technology (General) > T1-995 Technology (General) T Technology > T Technology (General) > T175-178 Industrial research. Research and development T Technology > T Technology (General) > T57.6-57.97 Operations research. Systems analysis
Divisions:	09-Faculty of Computer Science > 56201-Computer Systems (S1)
Depositing User:	Muhammad arief
Date Deposited:	01 Sep 2021 03:14
Last Modified:	01 Sep 2021 03:14
URI:	http://repository.unsri.ac.id/id/eprint/52750

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