{"id":"W2183681512","doi":"","title":"Exposure maps: removing reliance on attribution during scan detection","year":2006,"lang":"en","type":"article","venue":"USENIX conference on Hot topics in security","topic":"Network Security and Intrusion Detection","field":"Computer Science","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"","keywords":"Computer science; Footprint; Artificial intelligence; 3d scanning; Botnet; Event (particle physics); Real-time computing; Computer vision; The Internet","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":[0.005936917,0.001817914,0.001868821,0.004932227,0.001171391,0.003397392,0.003176669,0.002111997,0.002786614],"category_scores_gemma":[0.0618208,0.001474536,0.001093064,0.004002627,0.001921628,0.01084214,0.007280522,0.002334835,0.001712769],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007065082,"about_ca_system_score_gemma":0.002099833,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002976988,"about_ca_topic_score_gemma":0.002512146,"domain_scores_codex":[0.9928514,0.001911386,0.0004283899,0.001857247,0.002319051,0.000632576],"domain_scores_gemma":[0.9391499,0.02479848,0.005524247,0.0221398,0.007158267,0.001229264],"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":[0.001563788,0.0004652098,0.06035227,0.0004381764,0.0002693401,0.0006747455,0.002332407,0.06742699,0.01648517,0.0380825,0.007906689,0.8040027],"study_design_scores_gemma":[0.0001193831,0.0004972671,0.02196945,0.0001498572,0.0002385178,0.00130975,0.0009651406,0.816883,0.03897405,0.09876399,0.01992066,0.0002088683],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.06530532,0.0002471513,0.9234272,0.000320821,0.0001248925,0.0002230651,0.0004302543,0.006073223,0.003848154],"genre_scores_gemma":[0.6740866,0.0003009574,0.3194358,0.000199087,0.0002238031,0.0002776973,0.001046619,0.0009861432,0.003443198],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.005936917,"threshold_uncertainty_score":0.03139782,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0199645628808747,"score_gpt":0.238151142931682,"score_spread":0.2181865800508073,"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."}}