{"data":{"id":"db1a72db-c755-41fb-a213-c485e067b646","title":"Dual-Locking Learned AI Models: A PIN-Based Sparse QIM Watermarking and Adaptive Index Permutation Approach","summary":"Researchers developed a dual-locking security method for protecting trained neural networks by combining two techniques: a PIN (personal identification number)-based watermark embedded in the network's bias coefficients, and a cryptographic key that scrambles the network's internal index vectors. When locked without the correct key, the network becomes nearly non-functional (dropping accuracy below 10%), but unlocking with the right key fully restores its performance while keeping the ownership watermark hidden inside the model.","solution":"N/A -- no mitigation discussed in source.","labels":["research","security"],"sourceUrl":"http://ieeexplore.ieee.org/document/11269351","publishedAt":"2025-11-26T13:21:37.000Z","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":"2025-11-26T13:21:37.000Z","capecIds":null,"crossRefCount":0,"attackSophistication":"advanced","impactType":["integrity"],"aiComponentTargeted":"model","llmSpecific":false,"classifierConfidence":0.92,"researchCategory":"peer_reviewed","atlasIds":null}}