{"data":{"id":"f46dbc4b-3697-44d5-97aa-41f752395e89","title":"Security Threat Detection and Defense Theory of Intelligent Operation and Maintenance System for Rail Transit Based on Adversarial Machine Learning","summary":"This study proposes PGD-CLA-ADS, an adversarial machine learning framework for detecting and defending against threats to rail transit intelligent operation and maintenance systems. The model generates simulated attacks with enhanced PGD samples and uses a CNN-LSTM-attention network to extract attack features, then applies an adaptive defense for real-time response. Tested on public datasets, it reports 95.8% threat detection accuracy, a 2.1% false positive rate, and attack response latency within 0.3 s.","solution":"N/A -- no mitigation discussed in source.","labels":["security","research"],"sourceUrl":"https://doi.org/10.1002/spy2.70251","publishedAt":"2026-10-01T00:00:00.000Z","cveId":null,"cweIds":null,"cvssScore":null,"cvssSeverity":null,"severity":"info","attackType":["model_poisoning","model_evasion"],"issueType":"research","affectedPackages":null,"affectedPackageNames":null,"affectedPackageRefs":null,"affectedVendors":[],"affectedVendorsRaw":[],"classifierModel":"claude-haiku-5-5","classifierPromptVersion":"v4","summaryPromptVersion":"v2","headline":null,"headlinePromptVersion":null,"cvssVector":null,"attackVector":null,"attackComplexity":null,"privilegesRequired":null,"userInteraction":null,"exploitMaturity":null,"epssScore":null,"epssCheckedAt":null,"kevDateAdded":null,"advisoryAliases":null,"affectedPackagesSource":null,"affectedPackagesCheckedAt":null,"patchAvailable":null,"disclosureDate":"2026-10-01T00:00:00.000Z","capecIds":null,"crossRefCount":0,"attackSophistication":"advanced","impactType":["integrity","availability","safety"],"aiComponentTargeted":"model","llmSpecific":false,"classifierConfidence":0.85,"researchCategory":"peer_reviewed","atlasIds":null}}