{"data":{"id":"765c6396-7274-4b74-9d34-312e7bca21bc","title":"Weakly-Supervised Prompt-Guided Privacy Enhancement for Soft-Biometric Attributes in Facial Images","summary":"Researchers propose IFSNet, a weakly supervised, prompt-driven framework that enhances image-level privacy in face images by obscuring soft-biometric attributes such as age, gender, and race while preserving identity utility. It needs no per-image sensitive-attribute annotations during training or inference. The authors report that across five face datasets and three identity-labeled datasets, it reduces sensitive-attribute inference while retaining verification performance, measured by equal error rate and false non-match rate, with a favorable privacy-utility trade-off.","solution":"N/A -- no mitigation discussed in source.","labels":["privacy","research"],"sourceUrl":"http://ieeexplore.ieee.org/document/11711209","publishedAt":"2026-09-25T05:06:31.000Z","cveId":null,"cweIds":null,"cvssScore":null,"cvssSeverity":null,"severity":"info","attackType":[],"issueType":"research","affectedPackages":null,"affectedPackageNames":null,"affectedVendors":[],"affectedVendorsRaw":[],"classifierModel":"claude-haiku-5-5","classifierPromptVersion":"v4","summaryPromptVersion":"v2","cvssVector":null,"attackVector":null,"attackComplexity":null,"privilegesRequired":null,"userInteraction":null,"exploitMaturity":null,"epssScore":null,"epssCheckedAt":null,"kevDateAdded":null,"advisoryAliases":null,"affectedPackagesSource":null,"affectedPackagesCheckedAt":null,"patchAvailable":null,"disclosureDate":"2026-09-25T05:06:31.000Z","capecIds":null,"crossRefCount":0,"attackSophistication":"moderate","impactType":["confidentiality"],"aiComponentTargeted":"model","llmSpecific":false,"classifierConfidence":0.85,"researchCategory":"peer_reviewed","atlasIds":null}}