{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2022,7,29]],"date-time":"2022-07-29T08:28:37Z","timestamp":1659083317003},"reference-count":20,"publisher":"Hindawi Limited","license":[{"start":{"date-parts":[[2021,7,16]],"date-time":"2021-07-16T00:00:00Z","timestamp":1626393600000},"content-version":"unspecified","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Wireless Communications and Mobile Computing"],"published-print":{"date-parts":[[2021,7,16]]},"abstract":"When using differential privacy to publish high-dimensional data, the huge dimensionality leads to greater noise. Especially for high-dimensional binary data, it is easy to be covered by excessive noise. Most existing methods cannot address real high-dimensional data problems appropriately because they suffer from high time complexity. Therefore, in response to the problems above, we propose the differential privacy adaptive Bayesian network algorithm PrivABN to publish high-dimensional binary data. This algorithm uses a new greedy algorithm to accelerate the construction of Bayesian networks, which reduces the time complexity of the GreedyBayes algorithm from \n $\backslash n\mathrm{O\backslash /mi\backslash n\"(\"\backslash n{\backslash n\mathrm{n\backslash /mi\backslash n\mathrm{k\backslash /mi\backslash n\mathrm{C\backslash /mi\backslash n\; \backslash /mrow\backslash n\backslash n\mathrm{m\backslash /mi\backslash n+\backslash /mo\backslash n\mathrm{1\backslash /mn\backslash n\; \backslash /mrow\backslash n\backslash n\mathrm{k\backslash /mi\backslash n+\backslash /mo\backslash n\mathrm{2\backslash /mn\backslash n\; \backslash /mrow\backslash n\; \backslash /msubsup\backslash n\; \backslash /mrow\backslash n\; \backslash /mfenced\backslash n\; \backslash /math\backslash n\; \backslash /jats:inline-formula\; to\n \n O\/mi\n \n \n \n \n n\/mi\n m\/mi\n \/mrow\n \n 4\/mn\n \/mrow\n \/msup\n \/mrow\n \/mfenced\n \/math\n \/jats:inline-formula. In addition, it uses an adaptive algorithm to adjust the structure and uses a differential privacy Exponential mechanism to preserve the privacy, so as to generate a high-quality protected Bayesian network. Moreover, we use the Bayesian network to calculate the conditional distribution with noise and generate a synthetic dataset for publication. This synthetic dataset satisfies \n \n \epsilon \/mi\n \/math\n \/jats:inline-formula-differential privacy. Lastly, we carry out experiments against three real-life high-dimensional binary datasets to evaluate the functional performance.\/jats:p","DOI":"10.1155\/2021\/8693978","type":"journal-article","created":{"date-parts":[[2021,7,17]],"date-time":"2021-07-17T18:20:06Z","timestamp":1626546006000},"page":"1-11","source":"Crossref","is-referenced-by-count":1,"title":["Equation Chapter 1 Section 1 Differentially Private High-Dimensional Binary Data Publication via Adaptive Bayesian Network"],"prefix":"10.1155","volume":"2021","author":[{"ORCID":"http:\/\/orcid.org\/0000-0002-9583-6040","authenticated-orcid":true,"given":"Sun","family":"Lan","sequence":"first","affiliation":[{"name":"College of Mathematics and Computer Science, Fuzhou University, Fuzhou 350108, China"}]},{"ORCID":"http:\/\/orcid.org\/0000-0001-6596-8926","authenticated-orcid":true,"given":"Jinxin","family":"Hong","sequence":"additional","affiliation":[{"name":"College of Mathematics and Computer Science, Fuzhou University, Fuzhou 350108, China"}]},{"ORCID":"http:\/\/orcid.org\/0000-0002-3431-1857","authenticated-orcid":true,"given":"Junya","family":"Chen","sequence":"additional","affiliation":[{"name":"College of Mathematics and Computer Science, Fuzhou University, Fuzhou 350108, China"}]},{"ORCID":"http:\/\/orcid.org\/0000-0003-1575-8239","authenticated-orcid":true,"given":"Jianping","family":"Cai","sequence":"additional","affiliation":[{"name":"College of Mathematics and Computer Science, Fuzhou University, Fuzhou 350108, China"}]},{"ORCID":"http:\/\/orcid.org\/0000-0003-1826-6707","authenticated-orcid":true,"given":"Yilei","family":"Wang","sequence":"additional","affiliation":[{"name":"College of Mathematics and Computer Science, Fuzhou University, Fuzhou 350108, China"}]}],"member":"98","reference":[{"key":"1","doi-asserted-by":"publisher","DOI":"10.1142\/S0218488502001648"},{"key":"2","first-page":"754","article-title":"(\alpha , k)-anonymity: an enhanced k-anonymity model for privacy preserving data publishing","author":"R. C.-W. Wong"},{"key":"3","doi-asserted-by":"publisher","DOI":"10.1109\/ICDE.2007.367856"},{"key":"4","doi-asserted-by":"publisher","DOI":"10.1145\/1217299.1217302"},{"key":"5","doi-asserted-by":"crossref","article-title":"Differential privacy","author":"C. Dwork","year":"2006","DOI":"10.1007\/11787006_1"},{"key":"6","doi-asserted-by":"publisher","DOI":"10.1145\/331983.331986"},{"key":"7","doi-asserted-by":"publisher","DOI":"10.1109\/ICDM.2003.1250908"},{"key":"8","first-page":"1435","article-title":"Priview: practical differentially private release of marginal contingency tables","author":"W. Qardaji"},{"key":"9","doi-asserted-by":"crossref","article-title":"PrivBayes: private data release via bayesian networks","author":"J. Zhang","year":"2014","DOI":"10.1145\/2588555.2588573"},{"key":"10","doi-asserted-by":"publisher","DOI":"10.1145\/3134428"},{"issue":"10, article 2343","key":"11","article-title":"Privacy preserving data publishing via weighted bayesian networks","volume":"53","author":"W. Liang","year":"2016","journal-title":"Journal of Computer Research and Development"},{"key":"12","first-page":"129","article-title":"Differentially private high-dimensional data publication via sampling-based inference","author":"R. Chen"},{"issue":"12, article 2794","key":"13","article-title":"Private high-dimensional data publication with junction tree","volume":"55","author":"Z. Xiaojian","year":"2018","journal-title":"Journal of Computer Research and Development"},{"key":"14","first-page":"133","article-title":"Differentially private high-dimensional data publication via markov network","author":"F. Wei"},{"key":"15","first-page":"265","article-title":"Calibrating noise to sensitivity in private data analysis","author":"C. Dwork"},{"key":"16","first-page":"20","article-title":"Differentially private spatial decompositions","author":"G. Cormode"},{"key":"17","first-page":"19","article-title":"Privacy integrated queries: an extensible platform for privacy-preserving data analysis","author":"F. D. McSherry"},{"key":"18","volume-title":"National Long-Term Care Survey: 1982, 1984, 1989, 1994, 1999, and 2004","author":"K. G. Manton","year":"2010"},{"key":"19","volume-title":"Integrated public use microdata series: version 6.0 [dataset]","author":"S. Ruggles","year":"2015"},{"key":"20","author":"B. Tom"}],"container-title":["Wireless Communications and Mobile Computing"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/downloads.hindawi.com\/journals\/wcmc\/2021\/8693978.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/downloads.hindawi.com\/journals\/wcmc\/2021\/8693978.xml","content-type":"application\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/downloads.hindawi.com\/journals\/wcmc\/2021\/8693978.pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2021,7,17]],"date-time":"2021-07-17T18:20:12Z","timestamp":1626546012000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.hindawi.com\/journals\/wcmc\/2021\/8693978\/"}},"subtitle":[],"editor":[{"given":"Yong","family":"Zhang","sequence":"additional","affiliation":[]}],"short-title":[],"issued":{"date-parts":[[2021,7,16]]},"references-count":20,"alternative-id":["8693978","8693978"],"URL":"http:\/\/dx.doi.org\/10.1155\/2021\/8693978","relation":{},"ISSN":["1530-8677","1530-8669"],"issn-type":[{"value":"1530-8677","type":"electronic"},{"value":"1530-8669","type":"print"}],"subject":["Electrical and Electronic Engineering","Computer Networks and Communications","Information Systems"],"published":{"date-parts":[[2021,7,16]]}}}}}}}}}}}_{}^{}\")\"}$