Universiti Teknologi Malaysia Institutional Repository

Analysis of feature categories for malware visualization

Samy, Ganthan Narayana and Magalingam, Pritheega and Mohd. Ariffin, Aswami Fadillah and Mohd. Khairudin, Wafa and Md. Senan, Mohamad Firham Efendy and Yunos, Zahri (2018) Analysis of feature categories for malware visualization. Journal of Telecommunication, Electronic and Computer Engineering, 10 (3-2). pp. 1-5. ISSN 2180-1843

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Official URL: https://journal.utem.edu.my/index.php/jtec/article...

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.

Item Type:Article
Uncontrolled Keywords:features, malware, malware visualization, visualization tools
Subjects:Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Divisions:Advanced Informatics School
ID Code:85514
Deposited By: Yanti Mohd Shah
Deposited On:30 Jun 2020 16:49
Last Modified:30 Jun 2020 16:49

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