{"data":{"id":"91422276-1565-490a-a0e4-2a89bac05c13","title":"A Survey of Neural Network Robustness Assessment in Image Recognition","summary":"This academic survey paper reviews methods for testing how well neural networks (AI systems trained to recognize patterns in data) perform when faced with unexpected or manipulated images. The paper examines various approaches researchers use to assess whether image recognition systems remain accurate and reliable under challenging conditions.","solution":"N/A -- no mitigation discussed in source.","labels":["research","safety"],"sourceUrl":"https://dl.acm.org/doi/abs/10.1145/3814941?af=R","publishedAt":"2026-06-14T06:01:13.333Z","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":"moderate","impactType":["integrity","safety"],"aiComponentTargeted":"model","llmSpecific":false,"classifierConfidence":0.85,"researchCategory":"peer_reviewed","atlasIds":null}}