{"data":{"id":"c9053347-30d1-480f-a01d-02a74189f5ae","title":"Federated learning with update level noise perturbation and blockchain audit logging for privacy-preserving healthcare ECG classification","summary":"Researchers propose FedChainDP, a federated learning framework for ECG classification across hospitals that adds update-level Gaussian noise, encrypts updates with AES-256-GCM, and logs them on a blockchain with Merkle-tree integrity protection. On MIT-BIH data split across 5 hospitals, the model reached 98.91% ± 0.14% accuracy, but the authors state the evaluation used a beat-level random split with duplication-based balancing, and no formal (ε, δ)-differential privacy guarantee is claimed.","solution":"N/A -- no mitigation discussed in source.","labels":["research","privacy"],"sourceUrl":"https://doi.org/10.1038/s41598-026-75517-w","publishedAt":"2026-10-13T00:00:00.000Z","cveId":null,"cweIds":null,"cvssScore":null,"cvssSeverity":null,"severity":"info","attackType":[],"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":"2026-10-13T00:00:00.000Z","capecIds":null,"crossRefCount":0,"attackSophistication":"moderate","impactType":["confidentiality"],"aiComponentTargeted":"training_data","llmSpecific":false,"classifierConfidence":0.85,"researchCategory":"peer_reviewed","atlasIds":null}}