{"id":"W4360777615","doi":"10.5267/j.ijdns.2023.1.010","title":"Awareness model for minimizing the effects of social engineering attacks in web applications","year":2023,"lang":"en","type":"article","venue":"International Journal of Data and Network Science","topic":"Spam and Phishing Detection","field":"Computer Science","cited_by":30,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Zarqa University","keywords":"Phishing; Hacker; Computer science; Cybercrime; Identity theft; Crawling; Computer security; World Wide Web; Web page; Social engineering (security); Botnet; Web application security; Web crawler; Set (abstract data type); Internet privacy; The Internet; Web development","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001095656,0.00003723504,0.00006780413,0.0001392508,0.0001034012,0.0001058553,0.001766057,0.00001496602,1.058368e-7],"category_scores_gemma":[0.000121578,0.0000283102,0.00001852283,0.0005328114,0.00005593262,0.0007538012,0.000343175,0.00006811116,2.092911e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000181062,"about_ca_system_score_gemma":0.0001196866,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000001901744,"about_ca_topic_score_gemma":0.000006364393,"domain_scores_codex":[0.9993085,0.000009355523,0.0001725926,0.0001196812,0.0002866307,0.0001032424],"domain_scores_gemma":[0.9992352,0.0003408183,0.0001287681,0.0001330012,0.000139948,0.00002223944],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001026073,0.0001409615,0.01146538,0.0001528057,0.0001341433,0.00001991764,0.007591503,0.5347445,0.0388738,0.07460092,0.009741362,0.3224321],"study_design_scores_gemma":[0.0001620354,0.00001370637,0.002760582,0.00004081384,0.000002984225,0.000008844549,0.00001220194,0.9945539,0.0002543728,0.00128731,0.0008722473,0.00003097305],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1032926,0.0001000687,0.8949425,0.0008111233,0.0007414384,0.00008327443,0.000009108099,0.00001009185,0.000009807538],"genre_scores_gemma":[0.9902348,0.00007405059,0.009350019,0.00004155036,0.0002842332,0.000006115953,0.00000214854,0.000002005459,0.000005098931],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8869422,"threshold_uncertainty_score":0.3281804,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03568142230089785,"score_gpt":0.329797802291564,"score_spread":0.2941163799906662,"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."}}