{"id":"W3211661740","doi":"10.1109/tits.2021.3122368","title":"DLTIF: Deep Learning-Driven Cyber Threat Intelligence Modeling and Identification Framework in IoT-Enabled Maritime Transportation Systems","year":2021,"lang":"en","type":"article","venue":"IEEE Transactions on Intelligent Transportation Systems","topic":"Network Security and Intrusion Detection","field":"Computer Science","cited_by":88,"is_retracted":false,"has_abstract":true,"ca_institutions":"École de Technologie Supérieure; Université du Québec à Montréal","funders":"","keywords":"Computer security; Identification (biology); Computer science; Internet of Things; Scheme (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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0006193346,0.0004280882,0.0005336962,0.0005504542,0.0004507418,0.0005221405,0.0003914633,0.0004438712,0.00006475565],"category_scores_gemma":[0.00001413494,0.0004807271,0.000197851,0.001502849,0.00006473945,0.0008914368,0.000001277445,0.0009109487,0.00007916839],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002200252,"about_ca_system_score_gemma":0.00008882883,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008644474,"about_ca_topic_score_gemma":0.001669724,"domain_scores_codex":[0.9956738,0.0003828174,0.001604092,0.001103649,0.0007495469,0.0004860676],"domain_scores_gemma":[0.9981088,0.0002914356,0.0003092942,0.0005795295,0.0005023603,0.0002085568],"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":[0.00005938701,0.0002113683,0.0002868019,0.0002143557,0.00006426319,0.00004620444,0.004764832,0.9681849,0.0007906516,0.01104275,0.000003258262,0.01433117],"study_design_scores_gemma":[0.0002692566,0.0001212228,0.0006273073,0.0006972401,0.00006675297,0.0000319283,0.002115197,0.9857588,0.008542298,0.0009561221,0.000301658,0.0005121791],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.09440799,0.001105004,0.900691,0.0001154496,0.002538523,0.0007517763,0.00002885926,0.0003161748,0.00004524533],"genre_scores_gemma":[0.9950921,0.001981235,0.002020373,0.00004616686,0.0000935915,0.0003210877,0.00007514397,0.00004686438,0.0003234395],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9006841,"threshold_uncertainty_score":0.9997644,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02099352215465269,"score_gpt":0.2493534571106608,"score_spread":0.2283599349560081,"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."}}