{"id":"W4313152279","doi":"10.1504/ijics.2022.127169","title":"Data breach: analysis, countermeasures and challenges","year":2022,"lang":"en","type":"article","venue":"International Journal of Information and Computer Security","topic":"Information and Cyber Security","field":"Computer Science","cited_by":32,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of New Brunswick","funders":"","keywords":"Data breach; Computer security; Computer science; Government (linguistics); Big data; Countermeasure; Internet privacy; Data science; Data mining; Engineering","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.02380427,0.00130322,0.0009903829,0.01558031,0.00285836,0.008317781,0.002451873,0.003566389,0.001702949],"category_scores_gemma":[0.06428976,0.0008951699,0.00146987,0.00871687,0.005189506,0.01808391,0.00421573,0.005797044,0.0008385677],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003791947,"about_ca_system_score_gemma":0.007602768,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003207382,"about_ca_topic_score_gemma":0.003149178,"domain_scores_codex":[0.9677535,0.01127137,0.003720348,0.002662117,0.01323541,0.001357372],"domain_scores_gemma":[0.8814082,0.06843685,0.01646205,0.008337025,0.02387442,0.001481477],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001243503,0.0003873073,0.05421867,0.01326962,0.000335861,0.001061362,0.008071238,0.005545154,0.002373316,0.1285361,0.02668453,0.7593926],"study_design_scores_gemma":[0.00003320681,0.0008121746,0.05329148,0.04178539,0.0006549146,0.007467927,0.0847581,0.02512863,0.01336654,0.1489269,0.6232171,0.0005577487],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"empirical","genre_scores_codex":[0.1147565,0.530935,0.1452768,0.1416884,0.002061586,0.001588335,0.001631084,0.001131754,0.0609306],"genre_scores_gemma":[0.6279398,0.2744905,0.08191601,0.007794122,0.0008627055,0.0007399583,0.001366193,0.0002035174,0.004687182],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02380427,"threshold_uncertainty_score":0.1258905,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02725649646269666,"score_gpt":0.2583611267456642,"score_spread":0.2311046302829675,"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."}}