February 17, 2026

Datascapes: Sonification for Anomaly Detection in AI-Supported Networked Environments

paper

Frontiers in Computer Science · January 2024

  • Proposes a replicable design framework for sonifying anomaly detection in AI-monitored networks, tested on both a water distribution system and corporate internet infrastructure
  • Evaluated by eight cybersecurity experts in real-world conditions, confirming that continuous soundscape metaphors let operators detect anomalies peripherally without adding to the already overloaded visual channel
  • Argues explicitly that in real-time monitoring of networked systems, new solutions must not increase the burden on the visual channel — the ear is the underused observability interface

Sonification of Network Traffic Flow for Monitoring and Situational Awareness

paper

PLoS ONE (Debashi & Vickers) · April 2018

  • Maps TCP/IP packet header flags to a soundscape, letting network administrators hear anomalous traffic patterns without staring at dashboards — the ear as intrusion detection system
  • User study measured with NASA TLX showed that sonification delivered higher situational awareness with lower cognitive workload than equivalent visual monitoring, direct evidence the auditory channel outperforms dashboards for continuous monitoring
  • Open-source implementation (SoNSTAR) makes this a reproducible template for piping infrastructure telemetry into sound instead of graphs