| Title | Analysis of Visualization Techniques for Malware Detection |
| Publication Type | Conference Paper |
| Year of Publication | 2020 |
| Authors | Kartel, Anastasia, Novikova, Evgenia, Volosiuk, Aleksandr |
| Conference Name | 2020 IEEE Conference of Russian Young Researchers in Electrical and Electronic Engineering (EIConRus) |
| Keywords | Data visualization, Human Behavior, Information security, Malware, malware analysis, Predictive Metrics, privacy, pubcrawl, Resiliency, security, Task Analysis, Two dimensional displays, visual analytics, visualization |
| Abstract | Due to the steady growth of various sophisticated types of malware, different malware analysis systems are becoming more and more demanded. While there are various automatic approaches available to identify and detect malware, the malware analysis is still time-consuming process. The visualization-driven techniques may significantly increase the efficiency of the malware analysis process by involving human visual system which is a powerful pattern seeker. In this paper the authors reviewed different visualization methods, examined their features and tasks solved with their help. The paper presents the most commonly used approaches and discusses open challenges in malware visual analytics. |
| DOI | 10.1109/EIConRus49466.2020.9038910 |
| Citation Key | kartel_analysis_2020 |
Analysis of Visualization Techniques for Malware Detection