{"id":"W2069857456","doi":"10.1145/1993077.1993080","title":"Can the Utility of Anonymized Data be Used for Privacy Breaches?","year":2011,"lang":"en","type":"article","venue":"ACM Transactions on Knowledge Discovery from Data","topic":"Privacy-Preserving Technologies in Data","field":"Computer Science","cited_by":84,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"Office of Integrative Activities; Office of International Science and Engineering; Division of Information and Intelligent Systems; Research Grants Council, University Grants Committee","keywords":"Data publishing; Computer science; Data anonymization; Adversary; Anonymity; Information privacy; k-anonymity; Closeness; Internet privacy; Data mining; Computer security; Data science; Publishing; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.04078216,0.001009801,0.00203924,0.003541938,0.002891614,0.01012915,0.004005242,0.007099167,0.002915004],"category_scores_gemma":[0.1596208,0.001009293,0.001942677,0.006119642,0.01262315,0.03129663,0.007270992,0.006013757,0.001910177],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003098789,"about_ca_system_score_gemma":0.002641949,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008672254,"about_ca_topic_score_gemma":0.0004869439,"domain_scores_codex":[0.9372321,0.03898875,0.002675459,0.005175985,0.01391273,0.002014912],"domain_scores_gemma":[0.7945338,0.07921044,0.01081213,0.1047579,0.00952527,0.001160375],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0009675998,0.0001960548,0.01646381,0.0006551846,0.0006397338,0.0009428842,0.004228143,0.02973156,0.003289681,0.6696098,0.01728906,0.2559865],"study_design_scores_gemma":[0.00007523049,0.0002168803,0.002209065,0.0004855603,0.0001483319,0.001999051,0.002492058,0.04045432,0.01028277,0.8801966,0.06133516,0.0001050235],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1220613,0.009972642,0.6868676,0.1237842,0.00166768,0.0005527523,0.00219913,0.001549962,0.05134471],"genre_scores_gemma":[0.9130582,0.002738769,0.07262773,0.004907168,0.0007735603,0.0002442447,0.0005928378,0.0002940613,0.004763343],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.04078216,"threshold_uncertainty_score":0.2156793,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2143621106515954,"score_gpt":0.3377835758204947,"score_spread":0.1234214651688993,"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."}}