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DyMoN: A Post-Hoc Kinematic Approach for Detecting Anomalies in Dynamic Networks
A from-scratch kinematic model for anomaly detection in dynamic graphs. It tracks network evolution through physical motion metrics, calculating magnitude and direction scores—specifically isolating the tanh function for directionality. The model was benchmarked against DSEDN, JODIE, and STRIPE baselines to validate its motion-aware approach.