{"data":{"id":"51c35ae7-c88d-48b2-9f2e-16ad41bab410","title":"C-GAN: Medical Image Steganography Based on Convergent GANs With Localization","summary":"This paper presents C-GAN, a method for medical image steganography (hiding secret messages inside medical images in a way that is undetectable to observers) using GANs (generative adversarial networks, a type of AI system where two neural networks compete to improve each other). The researchers improved previous steganography approaches by using a special measurement called Zero-centered Wasserstein distance to make training more stable and by adding local regularization to increase how much data can be hidden while keeping images looking natural.","solution":"N/A -- no mitigation discussed in source.","labels":["research"],"sourceUrl":"http://ieeexplore.ieee.org/document/11433023","publishedAt":"2026-03-12T13:17:07.000Z","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":"2026-03-12T13:17:07.000Z","capecIds":null,"crossRefCount":0,"attackSophistication":"moderate","impactType":["integrity"],"aiComponentTargeted":"model","llmSpecific":false,"classifierConfidence":0.75,"researchCategory":"peer_reviewed","atlasIds":null}}