{"data":{"id":"e0c8105d-a991-4cfd-a893-503253726f85","title":"Enhancing EEG Signal-Based Emotion Recognition With Synthetic Data: Diffusion Model Approach","summary":"This research paper describes a method to improve emotion recognition using EEG (electroencephalography, a technology that measures electrical activity in the brain) by generating synthetic EEG data through a diffusion model (a type of AI that creates new data by gradually removing noise from random data). The proposed approach achieved up to 5.6% better accuracy in identifying emotions compared to traditional methods, helping address the problem of not having enough real EEG data for training these systems.","solution":"N/A -- no mitigation discussed in source.","labels":["research"],"sourceUrl":"http://ieeexplore.ieee.org/document/11285782","publishedAt":"2025-12-09T13:16:32.000Z","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":"2025-12-09T13:16:32.000Z","capecIds":null,"crossRefCount":0,"attackSophistication":"moderate","impactType":null,"aiComponentTargeted":"training_data","llmSpecific":false,"classifierConfidence":0.85,"researchCategory":"peer_reviewed","atlasIds":null}}