Universiti Teknologi Malaysia Institutional Repository

Visual analytics with decision tree on network traffic flow for botnet detection

Muhammad, Muhammad Khairul Rijal and Mohd. Azmi, Nurulhuda Firdaus and Amir Sjarif, Nilam Nur and Ismail, Saiful Adli and Ya’acob, Suraya and Che Mohd. Yusof, Rasimah (2018) Visual analytics with decision tree on network traffic flow for botnet detection. International Journal of Advances in Soft Computing and its Applications, 10 (3). pp. 73-91. ISSN 2074-2827


Official URL: http://home.ijasca.com/data/documents/4_Pg_72-91_V...


Visual analytics (VA) is an integral approach combining visualization, human factors, and data analysis. VA can synthesize information and derive insight from massive, dynamic, ambiguous and often conflicting data. Thus, help discover the expected and unexpected information. Moreover, the visualization could support the assessment in a timely period on which pre-emptive action can be taken. This paper discusses the implementation of visual analytics with decision tree model on network traffic flow for botnet detection. The discussion covers scenarios based on workstation, network traffic ranges and times. The experiment consists of data modeling, analytics and visualization using Microsoft PowerBI platform. Five different VA with different scenario for botnet detection is examined and analysis. From the studies, it may provide visual analytics as flexible approach for botnet detection on network traffic flow by being able to add more information related to botnet, increase path for data exploration and increase the effectiveness of analytics tool. Moreover, learning the pattern of communication and identified which is a normal behavior and abnormal behavior will be vital for security visual analyst as a future reference.

Item Type:Article
Uncontrolled Keywords:data visualization, decision tree, visual analytics
Subjects:T Technology > T Technology (General)
Divisions:Razak School of Engineering and Advanced Technology
ID Code:86502
Deposited By: Yanti Mohd Shah
Deposited On:30 Sep 2020 16:41
Last Modified:30 Sep 2020 16:41

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