Analysis of Feature Categories for Malware Visualization

Authors

  • Ganthan Narayana Samy Advanced Informatics School, Universiti Teknologi Malaysia (UTM AIS), Malaysia.
  • Pritheega Magalingam Advanced Informatics School, Universiti Teknologi Malaysia (UTM AIS), Malaysia.
  • Aswami Fadillah Mohd Ariffin Cyber Security Malaysia (CSM), Malaysia.
  • Wafa Mohd Khairudin Cyber Security Malaysia (CSM), Malaysia.
  • Mohamad Firham Efendy Md Senan Cyber Security Malaysia (CSM), Malaysia.
  • Zahri Hj Yunos Cyber Security Malaysia (CSM), Malaysia.

Keywords:

Features, Malware, Malware Visualization, Visualization Tools,

Abstract

It is important to know which features are more effective for certain visualization types. Furthermore, selecting an appropriate visualization tool plays a key role in descriptive, diagnostic, predictive and prescriptive analytics. Moreover, analyzing the activities of malicious scripts or codes is dependent on the extracted features. In this paper, the authors focused on reviewing and classifying the most common extracted features that have been used for malware visualization based on specified categories. This study examines the features categories and its usefulness for effective malware visualization. Additionally, it focuses on the common extracted features that have been used in the malware visualization domain. Therefore, the conducted literature review finding revealed that the features could be categorized into four main categories, namely, static, dynamic, hybrid, and application metadata. The contribution of this research paper is about feature selection for illustrating which features are effective with which visualization tools for malware visualization.

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Published

2018-09-26

How to Cite

Narayana Samy, G., Magalingam, P., Mohd Ariffin, A. F., Mohd Khairudin, W., Md Senan, M. F. E., & Hj Yunos, Z. (2018). Analysis of Feature Categories for Malware Visualization. Journal of Telecommunication, Electronic and Computer Engineering (JTEC), 10(3-2), 1–5. Retrieved from https://jtec.utem.edu.my/jtec/article/view/4703

Issue

Vol. 10 No. 3-2: Recent Trends in Computer Science and Information Technology

Section

Articles

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