{"data":{"id":"dfc1db65-67d7-46b5-81da-0ffe48064011","title":"Deepfake detection with dual-mode swin transformer: Multi-scale feature learning and local ambiguity mitigation","summary":"This research paper presents a method for detecting deepfakes (synthetic videos or images created by AI to look realistic) using a dual-mode Swin Transformer, which is a type of neural network architecture. The approach uses multi-scale feature learning (analyzing visual details at different zoom levels) and local ambiguity mitigation (reducing confusion in uncertain areas) to improve detection accuracy. This is a technical contribution to security research, not a response to an existing vulnerability or security incident.","solution":"N/A -- no mitigation discussed in source.","labels":["research","safety"],"sourceUrl":"https://www.sciencedirect.com/science/article/pii/S2214212626001523?dgcid=rss_sd_all","publishedAt":"2026-06-03T00:01:23.780Z","cveId":null,"cweIds":null,"cvssScore":null,"cvssSeverity":null,"severity":"info","attackType":[],"issueType":"research","affectedPackages":null,"affectedVendors":[],"affectedVendorsRaw":[],"classifierModel":"claude-haiku-4-5-20251001","classifierPromptVersion":"v3","cvssVector":null,"attackVector":null,"attackComplexity":null,"privilegesRequired":null,"userInteraction":null,"exploitMaturity":null,"epssScore":null,"patchAvailable":null,"disclosureDate":null,"capecIds":null,"crossRefCount":0,"attackSophistication":"moderate","impactType":["safety"],"aiComponentTargeted":"model","llmSpecific":false,"classifierConfidence":0.85,"researchCategory":"peer_reviewed","atlasIds":null}}