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All Journal JUTI: Jurnal Ilmiah Teknologi Informasi
Tofan, Yoga Ari
Institut Teknologi Sepuluh Nopember
Computer Science & IT Dentistry Education Library & Information Science

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MALICIOUS TRAFFIC DETECTION IN DNS INFRASTRUCTURE USING DECISION TREE ALGORITHM Thooriqoh, Hazna At; Azzmi, M. Naufal; Tofan, Yoga Ari; Shiddiqi, Ary Mazharuddin
JUTI: Jurnal Ilmiah Teknologi Informasi Vol. 20, No. 1, Januari 2022
Publisher : Department of Informatics, Institut Teknologi Sepuluh Nopember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/j24068535.v19i3.a1054

Abstract

Domain Name System (DNS) is an essential component in internet infrastructure to direct domains to IP addresses or conversely. Despite its important role in delivering internet services, attackers often use DNS as a bridge to breach a system. A DNS traffic analysis system is needed for early detection of attacks. However, the available security tools still have many shortcomings, for example broken authentication, sensitive data exposure, injection, etc. This research uses DNS analysis to develop anomaly-based techniques to detect malicious traffic on the DNS infrastructure. To do this, We look for network features that characterize DNS traffic. Features obtained will then be processed using the Decision Tree algorithm to classifyincoming DNS traffic. We experimented with 2.291.024 data traffic data matches the characteristics of BotNet and normal traffic. By dividing the data into 80% training and 20% testing data, our experimental results showed high detection aacuracy (96.36%) indicating the robustness of our method.
Co-Authors Ary Mazharuddin Shiddiqi Azzmi, M. Naufal Thooriqoh, Hazna At