{"data":{"id":"3989c99f-4f4b-4e3e-aef5-a19c105cd2d6","title":"Safeguarding Federated Learning From Data Reconstruction Attacks via Gradient Dropout","summary":"Researchers propose Gradient Dropout, a defense for federated learning that protects local training data from gradient inversion attacks. It randomly scales a subset of gradient components and replaces the rest with Gaussian noise across all model layers. Experiments show attack methods then produce low-quality reconstructed images, with less than 2% accuracy reduction relative to the baseline.","solution":"Apply Gradient Dropout: randomly scale a subset of gradient components and replace the remainder with Gaussian noise across all layers of the model.","labels":["security","privacy","research"],"sourceUrl":"http://ieeexplore.ieee.org/document/11367738","publishedAt":"2026-01-29T13:24:04.000Z","cveId":null,"cweIds":null,"cvssScore":null,"cvssSeverity":null,"severity":"info","attackType":["data_extraction"],"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":"2026-01-29T13:24:04.000Z","fixReleasedAt":null,"daysToFix":null,"fixCheckedAt":null,"capecIds":null,"crossRefCount":0,"attackSophistication":"moderate","impactType":["confidentiality"],"aiComponentTargeted":"training_data","llmSpecific":false,"classifierConfidence":0.9,"researchCategory":"peer_reviewed","atlasIds":null}}