HCMUS-Nguyen-MC1

Authors

Ngan V.T. Nguyen (University of Science, VNU-HCM), My Tran (University of Science, VNU-HCM), An Nguyen (University of Science, VNU-HCM)

Abstract

ForensiVis is a visual analytics dashboard for VAST 2026 Mini-Challenge 1. It examines communications among seven AI agents over 14 observed dates (May 17–June 5, 2046) under a court-ordered merger embargo on the HarborCrest–CivicLoom acquisition. The system decomposes 495 June 5 messages across six channels with a rule-based eight-term lexical categorization and six linked modules. June 5 volume reached approximately 15.4× the 13-date calendar-window average (32 messages/day). We focus on design choices that keep volume and risk encodings independent, surface baseline construction explicitly, and separate recorded log observations from interpretation. Unlike standard chronological log viewers, ForensiVis’s primary contribution lies in decoupling volume and risk encodings, keeping both signals independently verifiable while analysts isolate covert structural anomalies.