{"data":{"id":"fb8160ea-730e-445f-8e82-7ded691d4edb","title":"Wavelet-Guided Frequency-Domain Adaptive Learning: Balancing Adversarial Defense and High-Fidelity Image Reconstruction","summary":"WS-Net is a wavelet-guided frequency-domain adaptive denoising network for defending image classifiers against adversarial perturbations. It applies Discrete Wavelet Transform (DWT) and denoises only high-frequency components, using a Swin Network Denoiser (SND) trained with a multi-level loss. On ImageNet it reports 71.4% top-1 accuracy on clean images, 68.5% against CW attacks and 67.9% against DeepFool, with PSNR of 30.2 dB and SSIM of 0.87.","solution":"N/A -- no mitigation discussed in source.","labels":["security","research"],"sourceUrl":"https://doi.org/10.1142/s0218001426540121","publishedAt":"2026-09-30T00:00:00.000Z","cveId":null,"cweIds":null,"cvssScore":null,"cvssSeverity":null,"severity":"info","attackType":["model_evasion"],"issueType":"research","affectedPackages":null,"affectedPackageNames":null,"affectedPackageRefs":null,"affectedVendors":[],"affectedVendorsRaw":[],"classifierModel":"claude-haiku-5-5","classifierPromptVersion":"v4","summaryPromptVersion":"v2","headline":null,"headlinePromptVersion":null,"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":"2026-09-30T00:00:00.000Z","capecIds":null,"crossRefCount":0,"attackSophistication":"moderate","impactType":["integrity"],"aiComponentTargeted":"model","llmSpecific":false,"classifierConfidence":0.9,"researchCategory":"peer_reviewed","atlasIds":null}}