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All Journal JTIULM (Jurnal Teknologi Informasi Universitas Lambung Mangkurat)
Winda Andrini Wulandari
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Computer Science & IT Electrical & Electronics Engineering Engineering

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THE USE OF K-MEANS ALGORITHM ON DATALOG HONEYNET FOR PROFILING DDOS ATTACKS Winda Andrini Wulandari
Jurnal Teknologi Informasi Universitas Lambung Mangkurat (JTIULM) Vol. 2 No. 2 (2017)
Publisher : Fakultas Teknik Universitas Lambung Mangkurat

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (940.647 KB) | DOI: 10.20527/jtiulm.v2i2.17

Abstract

Cloud computing are admired for excellence, flexible benefits, and can be used together in various aspects and areas of business. According to Arbor Network that cloud technology is very vulnerable to DDoS attacks and the frequency of attacks has increased sharply in recent years.This research is the result of cooperation with AWN University and Indonesia Honeypot Project (IHP) Ministry of Communications and Informatics. The results suggest that honeynet as a way to protect and monitor the security of public cloud computing networks, and analyze its datalog through the k-means method approach to recognize cyber profilling DDoS attacks based on the timestamp recorded in the data.
THE ANALYSIS NETWORK FORENSICS USING HONEYPOT ON PUBLIC CLOUD COMPUTING SERVICE NETWORK Winda Andrini Wulandari
Jurnal Teknologi Informasi Universitas Lambung Mangkurat (JTIULM) Vol. 3 No. 1 (2018)
Publisher : Fakultas Teknik Universitas Lambung Mangkurat

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1126.435 KB) | DOI: 10.20527/jtiulm.v3i1.24

Abstract

This research presents visualization in dashboard using AWN campus honeypot log data connected to IHP (Kemkominfo) Jakarta on public cloud computing service network to categorize time stamp in data. Package attack data is divided into three categories namely morning, noon, and night based on Time Western Indonesia (WIB). DDoS attacks attacked several ports 21, 80, 135, and 445. K -means clustering method is implemented in this research to get categorization result of time of effective attack to know DDoS attack attack and cyber profilling which is expected to help monitoring process of anticipation of vulnerability cloud network of ddos / cyber crime attacks. The results of this study indicate that the method used to obtain results in accordance with the objectives.
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