{"data":{"id":"fcae3a0c-2b61-4cde-8ab7-3ab0552548ae","title":"Split Learning With Local Epoch Regulation and Time-Aware Detection","summary":"Researchers propose CoDefend, a split learning framework for edge computing that combines local epoch regulation with time-aware detection. The method assigns heterogeneous clients appropriate local epoch numbers and uses a detection window to identify malicious manipulation. Experiments on simulated and NVIDIA Jetson edge platforms show roughly 2× faster training than baselines, with comparable accuracy and effective detection even under collusion.","solution":"N/A -- no mitigation discussed in source.","labels":["security","research"],"sourceUrl":"http://ieeexplore.ieee.org/document/11415691","publishedAt":"2026-02-27T13:17:58.000Z","cveId":null,"cweIds":null,"cvssScore":null,"cvssSeverity":null,"severity":"info","attackType":["model_poisoning"],"issueType":"research","affectedPackages":null,"affectedPackageNames":null,"affectedPackageRefs":null,"affectedVendors":[],"affectedVendorsRaw":["NVIDIA Jetson"],"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":"2026-02-27T13:17:58.000Z","fixReleasedAt":null,"daysToFix":null,"fixCheckedAt":null,"capecIds":null,"crossRefCount":0,"attackSophistication":"moderate","impactType":["integrity","availability"],"aiComponentTargeted":"framework","llmSpecific":false,"classifierConfidence":0.8,"researchCategory":"peer_reviewed","atlasIds":null}}