{"data":{"id":"8c97b39f-7d51-40e0-8b08-9eeeb1efb343","title":"Label-Aware Distribution-Based Dynamic Weighting Aggregation for Hierarchical Backdoor Defense in Federated Learning","summary":"Researchers propose LADW (Label-Aware Distribution-based Dynamic Weighting), a black-box aggregation strategy for federated learning that defends against backdoor attacks without trusted client information. It uses a small auxiliary dataset, which may be synthetic data from a large text-to-image model, to infer each client's implicit label distribution from update similarity and reweight aggregation to suppress label-concentrated, potentially malicious updates. Experiments on multiple benchmarks report reduced attack success rates and preserved main-task accuracy, with state-of-the-art results under highly non-IID conditions.","solution":"N/A -- no mitigation discussed in source.","labels":["security","research"],"sourceUrl":"http://ieeexplore.ieee.org/document/11740705","publishedAt":"2026-10-19T05:06:46.000Z","cveId":null,"cweIds":null,"cvssScore":null,"cvssSeverity":null,"severity":"info","attackType":["model_poisoning"],"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":"2026-10-19T05:06:46.000Z","fixReleasedAt":null,"daysToFix":null,"fixCheckedAt":null,"capecIds":null,"crossRefCount":0,"attackSophistication":"advanced","impactType":["integrity"],"aiComponentTargeted":"training_data","llmSpecific":false,"classifierConfidence":0.9,"researchCategory":"peer_reviewed","atlasIds":null}}