{"id":"W4229879624","doi":"10.1109/glocom.2015.7417140","title":"Security-Enhanced Data Aggregation against Malicious Gateways in Smart Grid","year":2015,"lang":"en","type":"article","venue":"2015 IEEE Global Communications Conference (GLOBECOM)","topic":"Smart Grid Security and Resilience","field":"Engineering","cited_by":29,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ontario Tech University; University of Waterloo","funders":"","keywords":"Computer science; Homomorphic encryption; Data aggregator; Computer security; Cryptosystem; Cryptography; Smart grid; News aggregator; Paillier cryptosystem; Default gateway; Computer network; Information privacy; Energy consumption; Data integrity; Authentication (law); Scheme (mathematics); Encryption; Wireless sensor network; Engineering; Hybrid cryptosystem; Operating system","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":[0.0007369326,0.000336578,0.0003832154,0.0001258217,0.0001885768,0.0001744469,0.003809189,0.0002380571,0.00002654041],"category_scores_gemma":[0.0002225993,0.0003690775,0.00005335016,0.0008284002,0.0003056505,0.0008577069,0.0007832143,0.0006247261,0.0004448935],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000416564,"about_ca_system_score_gemma":0.0003203575,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008294319,"about_ca_topic_score_gemma":0.01371109,"domain_scores_codex":[0.9976974,0.0002855342,0.000620782,0.0004453358,0.0004037454,0.000547163],"domain_scores_gemma":[0.9950598,0.0001069065,0.0001176897,0.004089026,0.000307636,0.0003189399],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0003397528,0.003242941,0.04627445,0.0006994327,0.000612452,0.0001246311,0.01967712,0.1013818,0.005398459,0.05554999,0.663245,0.103454],"study_design_scores_gemma":[0.002784703,0.0001148065,0.006307927,0.0005656397,0.00007100855,0.00005680253,0.00308743,0.8259799,0.001888774,0.009630065,0.1477758,0.001737091],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8185305,0.007788033,0.01168214,0.003172745,0.005035762,0.001505978,0.001705586,0.001574964,0.1490043],"genre_scores_gemma":[0.9945467,0.002802755,0.001360888,0.0001545839,0.0001267661,0.00006006266,0.0008938875,0.00002376446,0.0000305548],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7245982,"threshold_uncertainty_score":0.9998761,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08496835250947447,"score_gpt":0.3131640900202471,"score_spread":0.2281957375107726,"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."}}