{"id":"W1605577974","doi":"10.1109/ccece.2015.7129455","title":"A realistic attack on SVD based watermarking scheme","year":2015,"lang":"en","type":"article","venue":"","topic":"Advanced Steganography and Watermarking Techniques","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Digital watermarking; Watermark; Computer science; Singular value decomposition; Scheme (mathematics); Class (philosophy); Attack model; Artificial intelligence; Image (mathematics); Computer security; Computer vision; Pattern recognition (psychology); Mathematics","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003262694,0.0001546769,0.0001359105,0.0001618083,0.00008651166,0.0001249592,0.0007376916,0.00005812003,0.000005430777],"category_scores_gemma":[0.00003772337,0.0001188524,0.00006596028,0.0003016302,0.00004211415,0.0003349426,0.0001477983,0.0001247967,0.00003962177],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004050821,"about_ca_system_score_gemma":0.00004035691,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001641793,"about_ca_topic_score_gemma":0.000002596259,"domain_scores_codex":[0.9988227,0.00006206609,0.000174214,0.0003518994,0.0002855514,0.0003035673],"domain_scores_gemma":[0.9989721,0.00006064879,0.00005401884,0.0006800663,0.00007878039,0.0001543633],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0003055319,0.0007436161,0.009541594,0.0001272959,0.00007982968,0.0008812601,0.001762622,0.002548598,0.003296023,0.7460338,0.1011715,0.1335083],"study_design_scores_gemma":[0.002278386,0.001215341,0.00128601,0.0003481794,0.00001408229,0.00008004103,0.00003744659,0.5398471,0.1218478,0.0980694,0.2333051,0.001671159],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.004972265,0.000014635,0.9525677,0.0009227436,0.0002078049,0.0001296226,0.000001304392,0.00123684,0.03994708],"genre_scores_gemma":[0.699014,0.00000146271,0.2992835,0.001353869,0.0000418243,0.00001778582,0.000004313773,0.000009176546,0.0002740794],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.6940417,"threshold_uncertainty_score":0.484666,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08580817026987926,"score_gpt":0.3132915422657946,"score_spread":0.2274833719959154,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}