Project information
- Name: Constellation Builder
- Category: Design
- Project URL: https://bit.ly/39BwM5G
VAST Challenge 2020: Mini-Challenge 3
The goal of the annual IEEE Visual Analytics Science and Technology (VAST) Challenge is to advance the field of visual analytics through competition.
Description
As a solution to the VAST Challenge 2020 Mini-Challenge 3, our team presents you ConstellationBuilder, a high-level situation-awareness and team assembly interface for cyber events. ConstellationBuilder aims to identify a range of different cyber-attack events as early as possible, determine their characteristics, and quickly assemble a team of white hat members with complementary skills to respond to each event. Specifically, the system clusters massive past reports and distills events based on their similarity of reports, then adopts collaborative filtering recommendations to suggest the most relevant events. After exploring the connection between historical events and team members who resolved the issues, our system recommends the most suitable team/constellation to handle each event. We call a team “constellation” because they shine like stars on solving cyber problems.
Team Members:
Prince Owusu Attah, Interaction Design, Purdue University, powusuat@purdue.edu
Lu Ding, Intelligent Visualization and Interaction Lab, Computer Graphics
Technology, Purdue University, ding241@purdue.edu
Xiaolei Guo, Intelligent Visualization and Interaction Lab, Computer Graphics
Technology, Purdue University, guo579@purdue.edu
Tianyi Zhang, College of Computer Science and Technology, Nanjing University of
Aeronautics and Astronautics, zhangtianyi@nuaa.edu.cn
Weiyue Deng, Intelligent Visualization and Interaction Lab, Computer Graphics
Technology, Purdue University, deng161@purdue.edu
Xuan Thao (Susie) Nguyen, School of Media Arts & Design, James Madison University,
nguyenxx@dukes.jmu.edu
Yunran Ju, Interaction Design, Purdue University, ju27@purdue.edu
Dr. Jieqiong Zhao, Electrical and Computer Engineering, Purdue University,
zhao413@purdue.edu
Dr. Chen Guo, School of Media Arts & Design, James Madison University,
guo4cx@jmu.edu
Dr. Zhenyu Cheryl Qian, Art and Design, Purdue University, qianz@purdue.edu
Dr. Yingjie Victor Chen, Intelligent Visualization and Interaction Lab, Computer
Graphics Technology, Purdue University, victorchen@purdue.edu
System Components
ConstellationBuilder is comprised of three core displays: report view, an event view, and a team constellation view (Fig. 2). All the views are visually linked by highlighting instances of the same object in one view.
The following mind map (Fig. 3) illustrate how ConstellationBuilder incorporates machine learning into the system and shows what uncertainties exist in both the data and the algorithms. For related reports, events, and experts, the uncertainties can be reflected in the similarity calculation. Therefore, our system recommends a list of reports, events, or experts ranking by similarity scores. Analysts can review the results and choose the most appropriate ones based on their knowledge.
Constellation Builder
Video walk-through of the system