{"data":{"id":"ae8ac64b-f20a-4abb-90c0-f44c2e4f60cb","title":"Robust Quantum Federated Learning Against Colluding and Non-Colluding Byzantine Attacks","summary":"This paper proposes a robust quantum federated learning method that defends against both colluding and non-colluding Byzantine attacks. It extends DBSCAN into an adaptive clustering-based defense with adaptive weight allocation, serving as a server-side robust aggregation mechanism. In experiments on MNIST and Fashion-MNIST, including label-flipping and backdoor attacks, MNIST accuracy reached 98%, a 38-percentage-point gain over the undefended baseline.","solution":"The proposed adaptive clustering-based defense algorithm, a server-side robust aggregation mechanism for quantum federated learning under mixed Byzantine attack settings.","labels":["security","research"],"sourceUrl":"http://ieeexplore.ieee.org/document/11612922","publishedAt":"2026-07-16T13:16:28.000Z","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":"2026-07-16T13:16:28.000Z","fixReleasedAt":null,"daysToFix":null,"fixCheckedAt":null,"capecIds":null,"crossRefCount":0,"attackSophistication":"advanced","impactType":["integrity"],"aiComponentTargeted":"framework","llmSpecific":false,"classifierConfidence":0.85,"researchCategory":"peer_reviewed","atlasIds":null}}