CAAD Reframes Time-Series Anomaly Detection as Granger-Causality Consistency Checking

arXiv·low signal

Most multivariate time-series anomaly detectors focus narrowly on temporal similarity of representations and overlook the disruption of internal causal relationships that actually characterizes system failures and latent anomalies. CAAD reframes detection as continuous verification of Granger-causality consistency using multi-scale alignment and structural causal consistency. Targeted at operational integrity monitoring for complex industrial systems.