[2604.02361] TRACE: Traceroute-based Internet Route change Analysis with Ensemble Learning

Computer Science > Networking and Internet Architecture arXiv:2604.02361 (cs) [Submitted on 21 Mar 2026] Title:TRACE: Traceroute-based Internet Route change Analysis with Ensemble Learning Authors:Raul Suzuki, Rodrigo Moreira, Pedro Henrique A. Damaso de Melo, Larissa F. Rodrigues Moreira, Flávio de Oliveira Silva View a PDF of the paper titled TRACE: Traceroute-based Internet Route change Analysis with Ensemble Learning, by Raul Suzuki and 4 other authors View PDF HTML (experimental) Abstract:Detecting Internet routing instability is a critical yet challenging task, particularly when relying solely on endpoint active measurements. This study introduces TRACE, a MachineLearning (ML)pipeline designed to identify route changes using only traceroute latency data, thereby ensuring independence from control plane information. We propose a robust feature engineering strategy that captures temporal dynamics using rolling statistics and aggregated context patterns. The architecture leverages a stacked ensemble of Gradient Boosted Decision Trees refined by a hyperparameter-optimized meta-learner. By strictly calibrating decision thresholds to address the inherent class imbalance of rare routing events, TRACE achieves a superior F1-score performance, significantly outperforming traditional baseline models and demonstrating strong effective ness in detecting routing changes on the Internet. Comments: Subjects: Networking and Internet Architecture (cs.NI); Artificial Intelligence (cs....