Malicious webshell family dataset for webshell multi-classification research

Zhao, Ying; Lv, Shenglan; Long, Woyun; Fan, Yilun; Yuan, Jian Lu; Jiang, Haojin; Zhou, Fangfang

doi:10.1016/j.visinf.2023.06.008

Cited by 15 publications

(2 citation statements)

References 54 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Directly displaying all edges in the view leads to severe overcrowding and overlap, resulting in visual clutter. Although there are methods to enhance the readability of the visual design [28], such as applying sampling methods [29] to the graph structures to retain only a few important structures, considering the task applicability (R2), we divide the edges in the RIN into "strong connections" and "weak connections" according to their weights. "Strong connections" refer to closer relationships between regional industries, such as the electronic device manufacturing industry in Sichuan Province and the battery manufacturing industry in Sichuan Province.…”

Section: Geographical Viewmentioning

confidence: 99%

V4RIN: visual analysis of regional industry network with domain knowledge

Xiong,

Yu,

Shi

et al. 2024

Vis. Comput. Ind. Biomed. Art

View full text Add to dashboard Cite

The regional industry network (RIN) is a type of financial network derived from industry networks that possess the capability to describe the connections between specific industries within a particular region. For most investors and financial analysts lacking extensive experience, the decision-support information provided by industry networks may be too vague. Conversely, RINs express more detailed and specific industry connections both within and outside the region. As RIN analysis is domain-specific and current financial network analysis tools are designed for generalized analytical tasks and cannot be directly applied to RINs, new visual analysis approaches are needed to enhance information exploration efficiency. In this study, we collaborated with domain experts and proposed V4RIN, an interactive visualization analysis system that integrates predefined domain knowledge and data processing methods to support users in uploading custom data. Through multiple views in the system panel, users can comprehensively explore the structure, geographical distribution, and spatiotemporal variations of the RIN. Two case studies were conducted and a set of expert interviews with five domain experts to validate the usability and reliability of our system.

show abstract

Section: Geographical Viewmentioning

confidence: 99%

V4RIN: visual analysis of regional industry network with domain knowledge

Xiong,

Yu,

Shi

et al. 2024

Vis. Comput. Ind. Biomed. Art

View full text Add to dashboard Cite

show abstract

“…The last limitation centers around the scalability of the visualization design, specifically when dealing with multidimensional data [61], time-series data [62], and large amounts of data. To surmount this limitation, interactive visualizations that allow users to zoom, filter, and interact could be included.…”

Section: Conclusion Limitations and Future Workmentioning

confidence: 99%

Datamator: An Authoring Tool for Creating Datamations via Data Query Decomposition

Guo,

Cao,

Cai

et al. 2023

Applied Sciences

View full text Add to dashboard Cite

Datamation is designed to animate an analysis pipeline step by step, serving as an intuitive and efficient method for interpreting data analysis outcomes and facilitating easy sharing with others. However, the creation of a datamation is a difficult task that demands expertise in diverse skills. To simplify this task, we introduce Datamator, a language-oriented authoring tool developed to support datamation generation. In this system, we develop a data query analyzer that enables users to generate an initial datamation effortlessly by inputting a data question in natural language. Then, the datamation is displayed in an interactive editor that affords users the ability to both edit the analysis progression and delve into the specifics of each step undertaken. Notably, the Datamator incorporates a novel calibration network that is able to optimize the outputs of the query decomposition network using a small amount of user feedback. To demonstrate the effectiveness of Datamator, we conduct a series of evaluations including performance validation, a controlled user study, and expert interviews.

show abstract