https://sunjiao123sun.github.io/2018/FraudVis/FraudVis.pdf?utm_source=chatgpt.com cyber fraud

Unique Title: “CyberFraudSight: A Visual Analytics Platform for Uncovering Coordinated Threat Actors in Online Transaction Networks” Abstract: The proliferation of orchestrated cyberfraud campaigns—such as click-farming, fake account registration, and credential stuffing—poses a significant threat to digital platforms. While unsupervised detection algorithms can identify suspicious group behaviors, their lack of interpretability hinders security analysts from validating and acting upon alerts. This paper introduces CyberFraudSight, an interactive visual analytics system designed to expose the inner workings of fraud detection models and reveal the behavioral fingerprints of coordinated malicious actors. The platform integrates multi-view visual profiling of fraud groups, temporal pattern analysis, intra-group network visualization, and feature importance mapping to support both forensic investigation and algorithm tuning. Through case studies on real-world social video and e-commerce platforms, we demonstrate how CyberFraudSight enables security teams to identify silence-and-burst attack patterns, shared infrastructure clusters, and cross-group synchronization—key indicators of professionally organized fraud operations. The system bridges the gap between automated detection and human-in-the-loop threat analysis, empowering organizations to respond more effectively to evolving cyberfraud tactics.