CA2: Cyber Attacks Analytics

TL;DR

CA2: Cyber Attacks Analytics is a visual system designed to analyze large anonymized graphs to identify responsible white hat groups behind cyber incidents, demonstrated through an iterative workflow for effective matching.

Contribution

The paper introduces CA2, a novel visual analytics system that enables efficient comparison and matching of subgraphs in large anonymized graphs for cyber attack attribution.

Findings

Effective identification of responsible groups in simulated cyber attack scenarios

Demonstrated iterative workflow enhances analysis accuracy

System handles extensive anonymized graph data efficiently

Abstract

The VAST Challenge 2020 Mini-Challenge 1 requires participants to identify the responsible white hat groups behind a fictional Internet outage. To address this task, we have created a visual analytics system named CA2: Cyber Attacks Analytics. This system is designed to efficiently compare and match subgraphs within an extensive graph containing anonymized profiles. Additionally, we showcase an iterative workflow that utilizes our system's capabilities to pinpoint the responsible group.