{"data":{"id":"08943e71-57ce-4d33-8724-a92120020c77","title":"Decentralized Federated Learning by Partial Message Exchange","summary":"This paper proposes PaME (DFL by Partial Message Exchange), a decentralized federated learning algorithm in which neighbor nodes exchange only randomly selected sparse coordinates. The authors state that this cuts communication costs and limits exposure of data-sensitive information, a property they characterize with a reconstruction-risk theory under partial observation. They prove linear-rate convergence in expectation to a stationary point under local Lipschitz continuity of the gradient and a doubly stochastic communication matrix, and report numerical experiments showing better performance than several decentralized learning baselines.","solution":"N/A -- no mitigation discussed in source.","labels":["research","privacy"],"sourceUrl":"http://ieeexplore.ieee.org/document/11646884","publishedAt":"2026-08-10T13:16:38.000Z","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":"2026-08-10T13:16:38.000Z","capecIds":null,"crossRefCount":0,"attackSophistication":"moderate","impactType":["confidentiality"],"aiComponentTargeted":"training_data","llmSpecific":false,"classifierConfidence":0.7,"researchCategory":"peer_reviewed","atlasIds":null}}