{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,26]],"date-time":"2026-02-26T06:32:30Z","timestamp":1772087550407,"version":"3.50.1"},"reference-count":45,"publisher":"MDPI AG","issue":"2","license":[{"start":{"date-parts":[[2026,2,15]],"date-time":"2026-02-15T00:00:00Z","timestamp":1771113600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100012166","name":"National Key Research and Development Program","doi-asserted-by":"publisher","award":["2018YFA0704703"],"award-info":[{"award-number":["2018YFA0704703"]}],"id":[{"id":"10.13039\/501100012166","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61972073, 61972215 and 62172238"],"award-info":[{"award-number":["61972073, 61972215 and 62172238"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100012226","name":"Fundamental Research Funds for the Central Universities of China","doi-asserted-by":"publisher","award":["252102210172"],"award-info":[{"award-number":["252102210172"]}],"id":[{"id":"10.13039\/501100012226","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Key Specialized Research and Development Program of Henan Province","award":["232102210071"],"award-info":[{"award-number":["232102210071"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Future Internet"],"abstract":"<jats:p>Existing Bayesian network-based differential privacy algorithms predominantly employ uniform privacy budget allocation. However, since attribute nodes carry heterogeneous information loads, the traditional privacy budget allocation strategy may result in insufficient noise being added to important attributes, while excessive noise is added to less important attributes. To optimize privacy budget utilization, we propose SA-PrivBayes, a scoring-function-driven allocation method. To enhance Bayesian network precision, we introduce a threshold mechanism during network construction that pre-filters low-scoring attribute pairs before applying the exponential mechanism for selection. Subsequently, during parameter learning, privacy budgets are dynamically allocated to low-dimensional attribute sets based on node-specific scoring functions. Under identical privacy budgets, our algorithm demonstrates stronger data protection capabilities compared to the PrivBayes algorithm. Experimental results indicate that, compared to traditional differential privacy methods based on Bayesian networks under identical privacy budgets, our algorithm better meets the privacy protection requirements of high-dimensional data while maintaining higher data utility.<\/jats:p>","DOI":"10.3390\/fi18020103","type":"journal-article","created":{"date-parts":[[2026,2,16]],"date-time":"2026-02-16T08:38:39Z","timestamp":1771231119000},"page":"103","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Differential Privacy Data Publication Based on Scoring Function"],"prefix":"10.3390","volume":"18","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-9388-5690","authenticated-orcid":false,"given":"Ke","family":"Yuan","sequence":"first","affiliation":[{"name":"School of Computer and Information Engineering, Henan University, Kaifeng 475004, China"},{"name":"Henan Provincial Engineering Research Center of Spatial Information Processing, Henan University, Kaifeng 475004, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Quan","family":"Zhang","sequence":"additional","affiliation":[{"name":"School of Computer and Information Engineering, Henan University, Kaifeng 475004, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5048-3536","authenticated-orcid":false,"given":"Yinghao","family":"Lin","sequence":"additional","affiliation":[{"name":"School of Computer and Information Engineering, Henan University, Kaifeng 475004, China"},{"name":"Henan Key Laboratory of Big Data Analysis and Processing, Henan University, Kaifeng 475001, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0853-140X","authenticated-orcid":false,"given":"Yuye","family":"Wang","sequence":"additional","affiliation":[{"name":"School of Computer and Information Engineering, Henan University, Kaifeng 475004, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Chunfu","family":"Jia","sequence":"additional","affiliation":[{"name":"School of Computer and Information Engineering, Henan University, Kaifeng 475004, China"},{"name":"College of Cryptology and Cyber Science, Nankai University, Tianjin 300350, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2026,2,15]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"347","DOI":"10.1016\/j.ins.2021.01.058","article-title":"Correlated tuple data release via differential privacy","volume":"560","author":"Wang","year":"2021","journal-title":"Inf. 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