Beyond Attack Success Rate: Representing Consistency in Evading the NIDS Feature-Space - Espindola, Allan da S.; Santin, Altair O.; Casimiro, António; Ferreira, Pedro M.; Viegas, Eduardo K. (Anais Estendidos do Simpósio Brasileiro de Cibersegurança (SBSeg), 2026)
Feature-space attacks directly modify NIDS inputs. Their attack success rate (ASR) measures classifier evasion under vector access but does not by itself establish an end-to-end NIDS vulnerability. We evaluate FGSM and PGD attacks against an MLP-based NIDS using ASR, Pearson correlation changes across records, and flow-level checks of features within each flow. ASR and correlation change followed distinct trajectories. At the largest perturbation limit, almost all successful volume-only and mixed evasions introduced a tested violation. In the packet-derived reference, no strong clean pair reversed sign, and no re-extracted record violated a tested relationship. Together, these findings show that correlation change and flow-level checks provide complementary evidence about representation consistency beyond classifier evasion.