Name
Title | ||
|---|---|---|
A collaborative visual analytics of trajectory and transaction data for digital forensics: VAST 2014 Mini-Challenge 2: Award for outstanding visualization and analysis. |
Abstract | ||
|---|---|---|
Advanced digital forensics technologies provide powerful basis in criminal investigation. Due to the complexity and diversity of data as well as the increasing quantity of the data, traditional digital forensics technologies have already can not adapt to the analysis requirements. This paper provides a visualization approach to analyze multiple types of data for digital forensics which provide users three interrelated tools: the RadViz tool, the PMViz tool and the SGGViz tool. Our solution focuses on the correlation analysis of trajectories and transactions, and it plays an important role in the process of analyzing the case in VAST 2014 Mini-challenge 2. |
Year | DOI | Venue |
|---|---|---|
2014 | 10.1109/VAST.2014.7042571 | IEEE VAST |
Keywords | Field | DocType |
transaction data,digital forensics,visual analysis,matrix,parallel coordinates | Data science,Data mining,Digital forensics,Visualization,Computer science,Visual analytics,Data type,Parallel coordinates,Criminal investigation,Transaction data,Trajectory | Conference |
ISSN | Citations | PageRank |
2325-9442 | 0 | 0.34 |
References | Authors | |
1 | 7 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Ying Zhao | 1 | 219 | 21.13 |
| Yanni Peng | 2 | 2 | 1.03 |
| Wei Huang | 3 | 2 | 0.72 |
| Yong Li | 4 | 88 | 22.09 |
| Fangfang Zhou | 5 | 42 | 3.67 |
| Zhifang Liao | 6 | 52 | 15.52 |
| Kang Zhang | 7 | 0 | 0.34 |