{"data":{"id":"6db146aa-167d-4cb3-a0c1-d3b66a693c0d","title":"AISM: Adversarial image steganography model for defending unauthorized recognition","summary":"Researchers have developed AISM (adversarial image steganography model, a technique that hides data inside images while making them resistant to AI recognition), a method for protecting images from being recognized by unauthorized AI systems. The approach uses adversarial techniques (methods that deliberately trick AI models by adding subtle, invisible changes to data) combined with steganography (the practice of hiding information within other data) to prevent unwanted AI analysis while keeping the images visually normal to humans. This work addresses privacy concerns where people want to prevent their images from being processed by AI systems without permission.","solution":"N/A -- no mitigation discussed in source.","labels":["security","research"],"sourceUrl":"https://www.sciencedirect.com/science/article/pii/S2214212626000839?dgcid=rss_sd_all","publishedAt":"2026-04-03T18:01:01.262Z","cveId":null,"cweIds":null,"cvssScore":null,"cvssSeverity":null,"severity":"info","attackType":["model_evasion"],"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":"advanced","impactType":["integrity","safety"],"aiComponentTargeted":"model","llmSpecific":false,"classifierConfidence":0.75,"researchCategory":"peer_reviewed","atlasIds":null}}