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 parameters, GSID employs an adaptive configuration encoder (ACE) that dynamically selects encoding strategies per parameter to preserve fine-grained numerical discrepancies. To expose the subtle inconsistencies of connected nodes and edges in the bipartite graph, GSID uses an inconsistency dynamic attention (IDA) mechanism that scores edges by drawing asymmetric attentions from both ends, rule compliance from one end and route connectivity from the other. It is demonstrated experimentally that GSID outperforms state-of-the-art baselines by threefold in F1 score and by 23.2% in accuracy. Ablation studies validate the effectiveness of both the ACE and IDA modules. Tests on unseen network scales and real-world network topologies show the superior adaptability of our GSID, compared to the baselines.

翻译：主权网络功能（例如路由协议）正日益复杂，且容易因协议配置异常和错误配置而引发故障。本文将协议配置异常检测问题解释为检测二分图中连接节点与边的结构不一致性，该二分图同时捕捉物理网络实体与逻辑协议状态。为此，我们提出了图结构不一致性检测器（GSID）模型以高效解决该问题。为应对协议配置参数的异构特性，GSID采用自适应配置编码器（ACE），该编码器根据参数动态选择编码策略，以保留细粒度的数值差异。为揭示二分图中连接节点与边的微妙不一致性，GSID使用不一致性动态注意力（IDA）机制，通过从两端分别施加非对称注意力（一端关注规则合规性，另一端关注路由连通性）对边进行评分。实验证明，GSID在F1分数上比最先进的基线方法高出三倍，在准确率上高出23.2%。消融研究验证了ACE和IDA模块的有效性。在未见过的网络规模与实际网络拓扑上的测试表明，与基线方法相比，我们的GSID具有更优的适应性。