{"data":{"id":"5d39b709-3c85-47b3-9a5f-5d943754446e","title":"Deep Supervised Adversarial Robust Hashing for Retrieval","summary":"Researchers propose Deep Supervised Adversarial Robust Hashing (DSARH), an end-to-end framework for deep hashing retrieval models. It uses similarity matrices and learnable hash codes to build gradient-based worst-case perturbations for adversarial training. Experiments on cross-modal and image retrieval show that existing deep hashing models are highly vulnerable to adversarial perturbations, while DSARH achieves better robust generalization and improves standard and adversarial performance on image-text benchmarks.","solution":"The proposed mitigation is adversarial training with the DSARH framework, which uses similarity matrices and learnable hash codes to generate worst-case perturbations for robust feature learning.","labels":["security","research"],"sourceUrl":"http://ieeexplore.ieee.org/document/11658958","publishedAt":"2026-08-18T13:16:06.000Z","cveId":null,"cweIds":null,"cvssScore":null,"cvssSeverity":null,"severity":"info","attackType":["model_evasion"],"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":"2026-08-18T13:16:06.000Z","capecIds":null,"crossRefCount":0,"attackSophistication":"advanced","impactType":["integrity","availability"],"aiComponentTargeted":"model","llmSpecific":false,"classifierConfidence":0.9,"researchCategory":"peer_reviewed","atlasIds":null}}