IMPROVING INTRUSION DETECTION SYSTEM TERHADAP SERANGAN PROBE MENGGUNAKAN HONEYPOT DI SMALL BOARD COMPUTER

FEBRIANDA, ARDIN and Stiawan, Deris and Heryanto, Ahmad (2020) IMPROVING INTRUSION DETECTION SYSTEM TERHADAP SERANGAN PROBE MENGGUNAKAN HONEYPOT DI SMALL BOARD COMPUTER. Undergraduate thesis, Sriwijaya University.

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Abstract

The focus of the study is to perform a collaboration of IDS system with honeypot and snort. It aims to improve the intrusion detection against probe attack where a probe is an attack that aims to collect information about targets such as host, port, and others. The pattern of the attack is obtained based on traffic analysis that will be tested using tools nessus and zenmap. The purpose of the result of the analysis is to find new rules that are needed to update the rules snort. The system will be installed in Banana Pi R1 as the router. In this study, scenario testing will produce 6 different datasets, consisting of normal datasets, attack datasets, and combined datasets. The test is carried out in two stages: (i) testing before updating the snort rules, and (ii) testing after updating the snort rules. The evaluation of detection results was carried out using the confusion matrix detection rate method, the first dataset before updating snort rules have an accuracy value of 61.90%, TPR 1.49%, and FPR 0.00%, while the first dataset after updating snort rules had a significant increase, it reaches 100% accuracy, TPR 100% and FPR 0.00%, the second dataset before updating the snort rules has an accuracy value of 59.98%, TPR 1.52%, and FPR 0.00%, while for the second dataset after updating the snort rules has the same value as the previous first dataset. It has 100% accuracy, TPR 100%, and FPR 0.00%.

Item Type:	Thesis (Undergraduate)
Uncontrolled Keywords:	Serangan Probe, IDS Snort, Honeypot, Banana Pi R1
Subjects:	Q Science > QA Mathematics > QA75-76.95 Calculating machines > QA75.5.A142 Computer science. Information society. Information technology. Q Science > QA Mathematics > QA75-76.95 Calculating machines > QA76.76.I58.A3115 Computer science. Computers. Intelligent agents (Computer software) Q Science > QA Mathematics > QA75-76.95 Calculating machines > QA76.9.A25 Computer security. Systems and Data Security.
Divisions:	09-Faculty of Computer Science > 56201-Computer Systems (S1)
Depositing User:	Users 9796 not found.
Date Deposited:	12 Jan 2021 08:31
Last Modified:	12 Jan 2021 08:31
URI:	http://repository.unsri.ac.id/id/eprint/39818

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