DETEKSI SERANGAN REMOTE TO LOCAL (R2L) MENGGUNAKAN METODE SUPPORT VECTOR MACHINE (SVM)

SAPUTRA, MUHAMMAD FACHRURROJI ILHAM and Stiawan, Deris (2019) DETEKSI SERANGAN REMOTE TO LOCAL (R2L) MENGGUNAKAN METODE SUPPORT VECTOR MACHINE (SVM). Undergraduate thesis, Sriwijaya Universty.

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Abstract

Detection is a process by which to examine or conduct an examination of something using certain means and techniques. The remote to local attack was a local incursion to get access to an account into a system that didn't have an account into that system before. The r2l attack patterns on darpa databases are identifiable with such parameters as source address, destination address, flags, IP addresses, and TCP claims. It USES vector support technology where SVM produces a classification of offensive and normal files separated by hyperlane line, purple class 1 for attack and -1 for normal yellow file. Results from my classification used SVM in evaluation with confusion matrix to find out how great the accuracy level of detection of attack and normal file and SVM. From this research we obtained a 99.99% accurate rate which is a very good result of accuracy.

Item Type:	Thesis (Undergraduate)
Uncontrolled Keywords:	Detection, Remote to Local, Snort IDS, Support Vectror Machine
Subjects:	Q Science > Q Science (General) > Q300-390 Cybernetics > Q325.5 Machine learning Q Science > Q Science (General) > Q350-390 Information theory T Technology > T Technology (General) > T57.6-57.97 Operations research. Systems analysis T Technology > TK Electrical engineering. Electronics Nuclear engineering > TK5101-6720 Telecommunication Including telegraphy, telephone, radio, radar, television > TK5105.5.S72 Computer networks
Divisions:	09-Faculty of Computer Science > 56201-Computer Systems (S1)
Depositing User:	Users 3931 not found.
Date Deposited:	06 Jan 2020 06:45
Last Modified:	06 Jan 2020 06:45
URI:	http://repository.unsri.ac.id/id/eprint/23108

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