{"paper":{"title":"Enhancing Network Resilience via Graph-Based Anomaly Detection in Sovereign Functions","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"GSID detects protocol configuration anomalies by identifying structural inconsistencies in a bipartite graph linking physical entities to logical states.","cross_cats":[],"primary_cat":"cs.NI","authors_text":"Chenhan Zhang, Massimo Piccardi, Raymond Owen, Wei Ni, Xin Hao","submitted_at":"2026-05-18T00:36:10Z","abstract_excerpt":"Sovereign network functions, e.g., routing protocols, are becoming increasingly complex and susceptible to failures arising from protocol configuration anomalies and anomalous configurations. This paper interprets the protocol configuration anomaly detection problem as detection of structural inconsistencies of connected nodes and edges in a bipartite graph that captures both physical network entities and logical protocol states. This graph structural inconsistency detector (GSID) model is proposed to solve the problem efficiently. To handle the heterogeneous nature of protocol configuration p"},"claims":{"count":4,"items":[{"kind":"strongest_claim","text":"It is demonstrated experimentally that GSID outperforms state-of-the-art baselines by threefold in F1 score and by 23.2% in accuracy.","source":"verdict.strongest_claim","status":"machine_extracted","claim_id":"C1","attestation":"unclaimed"},{"kind":"weakest_assumption","text":"The bipartite graph constructed from physical network entities and logical protocol states is assumed to capture the relevant structural inconsistencies that correspond to actual configuration anomalies without significant missing relationships or noise.","source":"verdict.weakest_assumption","status":"machine_extracted","claim_id":"C2","attestation":"unclaimed"},{"kind":"one_line_summary","text":"GSID applies an adaptive configuration encoder and inconsistency dynamic attention on bipartite graphs to detect protocol configuration anomalies, reporting threefold F1 improvement and 23.2% 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