{"id":"W4403944340","doi":"10.18280/ijsse.140530","title":"Enhancing Multi-Class Password Strength Prediction Through Machine Learning and Ensemble Techniques","year":2024,"lang":"en","type":"article","venue":"International Journal of Safety and Security Engineering","topic":"User Authentication and Security Systems","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Password; Computer science; Class (philosophy); Artificial intelligence; Machine learning; Ensemble learning; Computer security","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001365923,0.001085501,0.001269271,0.001402928,0.0004623801,0.0008149652,0.0007732843,0.0008232614,0.0009484947],"category_scores_gemma":[0.004121594,0.000279521,0.0008239756,0.0009025717,0.0001968906,0.001931694,0.0009679819,0.00158932,0.0009803623],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002610955,"about_ca_system_score_gemma":0.0004824481,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002005695,"about_ca_topic_score_gemma":0.00295791,"domain_scores_codex":[0.9990766,0.0001751149,0.00007283611,0.0001908394,0.0003593868,0.0001251156],"domain_scores_gemma":[0.9966697,0.001233579,0.0002744264,0.0004904862,0.001211357,0.0001203721],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0004174787,0.0007078813,0.01343443,0.00008380983,0.0002814474,0.0001452015,0.00008616065,0.1392033,0.03267208,0.0009414406,0.004180009,0.8078468],"study_design_scores_gemma":[0.000003234638,0.00006612354,0.001609491,0.000004414515,0.00003550897,0.00005254566,0.000009473273,0.99186,0.005666285,0.0003950178,0.0002879162,0.00001009227],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.144126,0.0006944296,0.8500621,0.0002296963,0.0002733041,0.00005145433,0.0001615862,0.002271425,0.00212986],"genre_scores_gemma":[0.8916063,0.0003060922,0.1049042,0.0001185111,0.0001399013,0.00003116548,0.0004000355,0.00007477878,0.002419021],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002005695,"threshold_uncertainty_score":0.007223785,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007699228376373904,"score_gpt":0.2443574096677576,"score_spread":0.2366581812913837,"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."}}